Constraints and spandrels of interareal connectomes

Science.gov (United States)

Rubinov, Mikail

2016-12-01

Interareal connectomes are whole-brain wiring diagrams of white-matter pathways. Recent studies have identified modules, hubs, module hierarchies and rich clubs as structural hallmarks of these wiring diagrams. An influential current theory postulates that connectome modules are adequately explained by evolutionary pressures for wiring economy, but that the other hallmarks are not explained by such pressures and are therefore less trivial. Here, we use constraint network models to test these postulates in current gold-standard vertebrate and invertebrate interareal-connectome reconstructions. We show that empirical wiring-cost constraints inadequately explain connectome module organization, and that simultaneous module and hub constraints induce the structural byproducts of hierarchies and rich clubs. These byproducts, known as spandrels in evolutionary biology, include the structural substrate of the default-mode network. Our results imply that currently standard connectome characterizations are based on circular analyses or double dipping, and we emphasize an integrative approach to future connectome analyses for avoiding such pitfalls.

The Budapest Reference Connectome Server v2.0.

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Szalkai, Balázs; Kerepesi, Csaba; Varga, Bálint; Grolmusz, Vince

2015-05-19

The connectomes of different human brains are pairwise distinct: we cannot talk about an abstract "graph of the brain". Two typical connectomes, however, have quite a few common graph edges that may describe the same connections between the same cortical areas. The Budapest Reference Connectome Server v2.0 generates the common edges of the connectomes of 96 distinct cortexes, each with 1015 vertices, computed from 96 MRI data sets of the Human Connectome Project. The user may set numerous parameters for the identification and filtering of common edges, and the graphs are downloadable in both csv and GraphML formats; both formats carry the anatomical annotations of the vertices, generated by the FreeSurfer program. The resulting consensus graph is also automatically visualized in a 3D rotating brain model on the website. The consensus graphs, generated with various parameter settings, can be used as reference connectomes based on different, independent MRI images, therefore they may serve as reduced-error, low-noise, robust graph representations of the human brain. The webserver is available at http://connectome.pitgroup.org. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Cerebral cartography and connectomics.

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Sporns, Olaf

2015-05-19

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

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Makropoulos, Antonios; Robinson, Emma C; Schuh, Andreas; Wright, Robert; Fitzgibbon, Sean; Bozek, Jelena; Counsell, Serena J; Steinweg, Johannes; Vecchiato, Katy; Passerat-Palmbach, Jonathan; Lenz, Gregor; Mortari, Filippo; Tenev, Tencho; Duff, Eugene P; Bastiani, Matteo; Cordero-Grande, Lucilio; Hughes, Emer; Tusor, Nora; Tournier, Jacques-Donald; Hutter, Jana; Price, Anthony N; Teixeira, Rui Pedro A G; Murgasova, Maria; Victor, Suresh; Kelly, Christopher; Rutherford, Mary A; Smith, Stephen M; Edwards, A David; Hajnal, Joseph V; Jenkinson, Mark; Rueckert, Daniel

2018-06-01

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

A hybrid CPU-GPU accelerated framework for fast mapping of high-resolution human brain connectome.

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Yu Wang

Full Text Available Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome. Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson's Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states.

An extensive assessment of network alignment algorithms for comparison of brain connectomes.

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Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

2017-06-06

Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

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Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

The Connectome Viewer Toolkit: an open source framework to manage, analyze and visualize connectomes

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Stephan eGerhard

2011-06-01

Full Text Available Abstract Advanced neuroinformatics tools are required for methods of connectome mapping, analysis and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration and sharing. We have designed and implemented the Connectome Viewer Toolkit --- a set of free and extensible open-source neuroimaging tools written in Python. The key components of the toolkit are as follows: 1. The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. 2. The Connectome File Format Library enables management and sharing of connectome files. 3. The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/.

Simultaneous estimation of the in-mean and in-variance causal connectomes of the human brain.

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Duggento, A; Passamonti, L; Guerrisi, M; Toschi, N

2017-07-01

In recent years, the study of the human connectome (i.e. of statistical relationships between non spatially contiguous neurophysiological events in the human brain) has been enormously fuelled by technological advances in high-field functional magnetic resonance imaging (fMRI) as well as by coordinated world wide data-collection efforts like the Human Connectome Project (HCP). In this context, Granger Causality (GC) approaches have recently been employed to incorporate information about the directionality of the influence exerted by a brain region on another. However, while fluctuations in the Blood Oxygenation Level Dependent (BOLD) signal at rest also contain important information about the physiological processes that underlie neurovascular coupling and associations between disjoint brain regions, so far all connectivity estimation frameworks have focused on central tendencies, hence completely disregarding so-called in-variance causality (i.e. the directed influence of the volatility of one signal on the volatility of another). In this paper, we develop a framework for simultaneous estimation of both in-mean and in-variance causality in complex networks. We validate our approach using synthetic data from complex ensembles of coupled nonlinear oscillators, and successively employ HCP data to provide the very first estimate of the in-variance connectome of the human brain.

Meta-connectomics: human brain network and connectivity meta-analyses.

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Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Toward a standardized structural-functional group connectome in MNI space.

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Horn, Andreas; Blankenburg, Felix

2016-01-01

The analysis of the structural architecture of the human brain in terms of connectivity between its subregions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute-Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. In a second analysis, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to others' findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) performing fiber tracking directly within MNI space. Such an approach may be used for various purposes like the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step toward a standard DTI template of the human brain

Local connectome phenotypes predict social, health, and cognitive factors

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Michael A. Powell

2018-03-01

Full Text Available The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N = 841 of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions. The local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size within a voxel, and it reflects the proximal characteristics of white matter fascicles distributed throughout the brain. Here we show how variability in the local connectome is correlated in a principled way across individuals. This intersubject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This work shows, for the first time, how the local connectome has both the sensitivity and the specificity to

Graph theoretical model of a sensorimotor connectome in zebrafish.

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Stobb, Michael; Peterson, Joshua M; Mazzag, Borbala; Gahtan, Ethan

2012-01-01

Mapping the detailed connectivity patterns (connectomes) of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line sensorimotor pathway in zebrafish. The model includes 2,616 neurons and 167,114 synaptic connections. Model neurons represent known cell types in zebrafish larvae, and connections were set stochastically following rules based on biological literature. Thus, our model is a uniquely detailed computational representation of a vertebrate connectome. The connectome has low overall connection density, with 2.45% of all possible connections, a value within the physiological range. We used graph theoretical tools to compare the zebrafish connectome graph to small-world, random and structured random graphs of the same size. For each type of graph, 100 randomly generated instantiations were considered. Degree distribution (the number of connections per neuron) varied more in the zebrafish graph than in same size graphs with less biological detail. There was high local clustering and a short average path length between nodes, implying a small-world structure similar to other neural connectomes and complex networks. The graph was found not to be scale-free, in agreement with some other neural connectomes. An experimental lesion was performed that targeted three model brain neurons, including the Mauthner neuron, known to control fast escape turns. The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome.

Graph theoretical model of a sensorimotor connectome in zebrafish.

Directory of Open Access Journals (Sweden)

Michael Stobb

Full Text Available Mapping the detailed connectivity patterns (connectomes of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line sensorimotor pathway in zebrafish. The model includes 2,616 neurons and 167,114 synaptic connections. Model neurons represent known cell types in zebrafish larvae, and connections were set stochastically following rules based on biological literature. Thus, our model is a uniquely detailed computational representation of a vertebrate connectome. The connectome has low overall connection density, with 2.45% of all possible connections, a value within the physiological range. We used graph theoretical tools to compare the zebrafish connectome graph to small-world, random and structured random graphs of the same size. For each type of graph, 100 randomly generated instantiations were considered. Degree distribution (the number of connections per neuron varied more in the zebrafish graph than in same size graphs with less biological detail. There was high local clustering and a short average path length between nodes, implying a small-world structure similar to other neural connectomes and complex networks. The graph was found not to be scale-free, in agreement with some other neural connectomes. An experimental lesion was performed that targeted three model brain neurons, including the Mauthner neuron, known to control fast escape turns. The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome.

Mapping the Alzheimer's brain with connectomics

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Teng eXie

2012-01-01

Full Text Available Alzheimer’s disease (AD is the most common form of dementia. As an incurable, progressive and neurodegenerative disease, it causes cognitive and memory deficits. However, the biological mechanisms underlying the disease are not thoroughly understood. In recent years, non-invasive neuroimaging and neurophysiological techniques (e.g., structural MRI, diffusion MRI, functional MRI and EEG/MEG and graph theory based network analysis have provided a new perspective on structural and functional connectivity patterns of the human brain (i.e., the human connectome in health and disease. Using these powerful approaches, several recent studies of patients with AD exhibited abnormal topological organization in both global and regional properties of neuronal networks, indicating that AD not only affects specific brain regions, but also alters the structural and functional associations between distinct brain regions. Specifically, disruptive organization in the whole-brain networks in AD is involved in the loss of small-world characters and the re-organization of hub distributions. These aberrant neuronal connectivity patterns were associated with cognitive deficits in patients with AD, even with genetic factors in healthy aging. These studies provide empirical evidence to support the existence of an aberrant connectome of AD. In this review we will summarize recent advances discovered in large-scale brain network studies of AD, mainly focusing on graph theoretical analysis of brain connectivity abnormalities. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis and monitoring.

Connectomic intermediate phenotypes for psychiatric disorders

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Alex eFornito

2012-04-01

Full Text Available Psychiatric disorders are phenotypically heterogeneous entities with a complex genetic basis. To mitigate this complexity, many investigators study so-called intermediate phenotypes that putatively provide a more direct index of the physiological effects of candidate genetic risk variants than overt psychiatric syndromes. Magnetic resonance imaging (MRI is a particularly popular technique for measuring such phenotypes because it allows interrogation of diverse aspects of brain structure and function in vivo. Much of this work however, has focused on relatively simple measures that quantify variations in the physiology or tissue integrity of specific brain regions in isolation, contradicting an emerging consensus that most major psychiatric disorders do not arise from isolated dysfunction in one or a few brain regions, but rather from disturbed interactions within and between distributed neural circuits; i.e., they are disorders of brain connectivity. The recent proliferation of new MRI techniques for comprehensively mapping the entire connectivity architecture of the brain, termed the human connectome, has provided a rich repertoire of tools for understanding how genetic variants implicated in mental disorder impact distinct neural circuits. In this article, we review research using these connectomic techniques to understand how genetic variation influences the connectivity and topology of human brain networks. We highlight recent evidence from twin and imaging genetics studies suggesting that the penetrance of candidate risk variants for mental illness, such as those in SLC6A4, MAOA, ZNF804A and APOE, may be higher for intermediate phenotypes characterised at the level of distributed neural systems than at the level of spatially localised brain regions. The findings indicate that imaging connectomics provides a powerful framework for understanding how genetic risk for psychiatric disease is expressed through altered structure and function of

Connectome organization is related to longitudinal changes in general functioning, symptoms and IQ in chronic schizophrenia

NARCIS (Netherlands)

Collin, G.; de Nijs, J.; Hulshoff Pol, H. E.; Cahn, W.; van den Heuvel, M. P.

2016-01-01

Emerging evidence suggests schizophrenia to involve widespread alterations in the macroscale wiring architecture of the human connectome. Recent findings of attenuated connectome alterations in unaffected siblings of schizophrenia patients suggest that altered connectome organization may relate to

Cerebral cartography and connectomics

OpenAIRE

Sporns, Olaf

2015-01-01

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamic...

The braingraph.org database of high resolution structural connectomes and the brain graph tools.

Science.gov (United States)

Kerepesi, Csaba; Szalkai, Balázs; Varga, Bálint; Grolmusz, Vince

2017-10-01

Based on the data of the NIH-funded Human Connectome Project, we have computed structural connectomes of 426 human subjects in five different resolutions of 83, 129, 234, 463 and 1015 nodes and several edge weights. The graphs are given in anatomically annotated GraphML format that facilitates better further processing and visualization. For 96 subjects, the anatomically classified sub-graphs can also be accessed, formed from the vertices corresponding to distinct lobes or even smaller regions of interests of the brain. For example, one can easily download and study the connectomes, restricted to the frontal lobes or just to the left precuneus of 96 subjects using the data. Partially directed connectomes of 423 subjects are also available for download. We also present a GitHub-deposited set of tools, called the Brain Graph Tools, for several processing tasks of the connectomes on the site http://braingraph.org.

Memory-Efficient Analysis of Dense Functional Connectomes.

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Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to

Data Dictionary Services in XNAT and the Human Connectome Project

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Rick eHerrick

2014-07-01

Full Text Available The XNAT informatics platform is an open source data management tool used by biomedical imaging researchers around the world. An important feature of XNAT is its highly extensible architecture: users of XNAT can add new data types to the system to capture the imaging and phenotypic data generated in their studies. Until recently, XNAT has had limited capacity to broadcast the meaning of these data extensions to users, other XNAT installations, and other software.We have implemented a data dictionary service for XNAT, which is currently being used on ConnectomeDB, the Human Connectome Project (HCP public data sharing website. The data dictionary service provides a framework to define key relationships between data elements and structures across the XNAT installation. This includes not just core data representing medical imaging data or subject or patient evaluations, but also taxonomical structures, security relationships, subject groups, and research protocols. The data dictionary allows users to define metadata for data structures and their properties, such as value types (e.g. textual, integers, floats and valid value templates, ranges, or field lists. The service provides compatibility and integration with other research data management services by enabling easy migration of XNAT data to standards-based formats such as RDF, JSON, and XML. It also facilitates the conversion of XNAT’s native data schema into standard neuroimaging ontology structures and provenances.

Memory-efficient analysis of dense functional connectomes

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Kristian Loewe

2016-11-01

Full Text Available The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software are compared with regard to their computational efficiency in terms of memory requirements and computation time. The matrix implementation based on on-demand computations has very low memory requirements thus enabling

Data dictionary services in XNAT and the Human Connectome Project

Science.gov (United States)

Herrick, Rick; McKay, Michael; Olsen, Timothy; Horton, William; Florida, Mark; Moore, Charles J.; Marcus, Daniel S.

2014-01-01

The XNAT informatics platform is an open source data management tool used by biomedical imaging researchers around the world. An important feature of XNAT is its highly extensible architecture: users of XNAT can add new data types to the system to capture the imaging and phenotypic data generated in their studies. Until recently, XNAT has had limited capacity to broadcast the meaning of these data extensions to users, other XNAT installations, and other software. We have implemented a data dictionary service for XNAT, which is currently being used on ConnectomeDB, the Human Connectome Project (HCP) public data sharing website. The data dictionary service provides a framework to define key relationships between data elements and structures across the XNAT installation. This includes not just core data representing medical imaging data or subject or patient evaluations, but also taxonomical structures, security relationships, subject groups, and research protocols. The data dictionary allows users to define metadata for data structures and their properties, such as value types (e.g., textual, integers, floats) and valid value templates, ranges, or field lists. The service provides compatibility and integration with other research data management services by enabling easy migration of XNAT data to standards-based formats such as the Resource Description Framework (RDF), JavaScript Object Notation (JSON), and Extensible Markup Language (XML). It also facilitates the conversion of XNAT's native data schema into standard neuroimaging vocabularies and structures. PMID:25071542

Aberrant brain functional connectome in patients with obstructive sleep apnea.

Science.gov (United States)

Chen, Li-Ting; Fan, Xiao-Le; Li, Hai-Jun; Ye, Cheng-Long; Yu, Hong-Hui; Xin, Hui-Zhen; Gong, Hong-Han; Peng, De-Chang; Yan, Li-Ping

2018-01-01

Obstructive sleep apnea (OSA) is accompanied by widespread abnormal spontaneous regional activity related to cognitive deficits. However, little is known about the topological properties of the functional brain connectome of patients with OSA. This study aimed to use the graph theory approaches to investigate the topological properties and functional connectivity (FC) of the functional connectome in patients with OSA, based on resting-state functional magnetic resonance imaging (rs-fMRI). Forty-five male patients with newly diagnosed untreated severe OSA and 45 male good sleepers (GSs) underwent a polysomnography (PSG), clinical evaluations, and rs-fMRI scans. The automated anatomical labeling (AAL) atlas was used to construct the functional brain connectome. The topological organization and FC of brain functional networks in patients with OSA were characterized using graph theory methods and investigated the relationship between functional network topology and clinical variables. Both the patients with OSA and the GSs exhibited high-efficiency "small-world" network attributes. However, the patients with OSA exhibited decreased σ, γ, E glob ; increased Lp, λ; and abnormal nodal centralities in several default-mode network (DMN), salience network (SN), and central executive network (CEN) regions. However, the patients with OSA exhibited abnormal functional connections between the DMN, SN, and CEN. The disrupted FC was significantly positive correlations with the global network metrics γ and σ. The global network metrics were significantly correlated with the Epworth Sleepiness Scale (ESS) score, Montreal Cognitive Assessment (MoCA) score, and oxygen desaturation index. The findings suggest that the functional connectome of patients with OSA exhibited disrupted functional integration and segregation, and functional disconnections of the DMN, SN, and CEN. The aberrant topological attributes may be associated with disrupted FC and cognitive functions. These

Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints.

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Fang-Cheng Yeh

2016-11-01

Full Text Available Quantifying differences or similarities in connectomes has been a challenge due to the immense complexity of global brain networks. Here we introduce a noninvasive method that uses diffusion MRI to characterize whole-brain white matter architecture as a single local connectome fingerprint that allows for a direct comparison between structural connectomes. In four independently acquired data sets with repeated scans (total N = 213, we show that the local connectome fingerprint is highly specific to an individual, allowing for an accurate self-versus-others classification that achieved 100% accuracy across 17,398 identification tests. The estimated classification error was approximately one thousand times smaller than fingerprints derived from diffusivity-based measures or region-to-region connectivity patterns for repeat scans acquired within 3 months. The local connectome fingerprint also revealed neuroplasticity within an individual reflected as a decreasing trend in self-similarity across time, whereas this change was not observed in the diffusivity measures. Moreover, the local connectome fingerprint can be used as a phenotypic marker, revealing 12.51% similarity between monozygotic twins, 5.14% between dizygotic twins, and 4.51% between none-twin siblings, relative to differences between unrelated subjects. This novel approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome.

Connectome analysis for pre-operative brain mapping in neurosurgery

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Hart, Michael G.; Price, Stephen J.; Suckling, John

2016-01-01

Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756

Connectome analysis for pre-operative brain mapping in neurosurgery.

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Hart, Michael G; Price, Stephen J; Suckling, John

2016-10-01

Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains 'wiring diagram'. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal-parietal-occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits.

Sex differences in the structural connectome of the human brain.

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Ingalhalikar, Madhura; Smith, Alex; Parker, Drew; Satterthwaite, Theodore D; Elliott, Mark A; Ruparel, Kosha; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

2014-01-14

Sex differences in human behavior show adaptive complementarity: Males have better motor and spatial abilities, whereas females have superior memory and social cognition skills. Studies also show sex differences in human brains but do not explain this complementarity. In this work, we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged 8-22 y, 428 males and 521 females) and discovered unique sex differences in brain connectivity during the course of development. Connection-wise statistical analysis, as well as analysis of regional and global network measures, presented a comprehensive description of network characteristics. In all supratentorial regions, males had greater within-hemispheric connectivity, as well as enhanced modularity and transitivity, whereas between-hemispheric connectivity and cross-module participation predominated in females. However, this effect was reversed in the cerebellar connections. Analysis of these changes developmentally demonstrated differences in trajectory between males and females mainly in adolescence and in adulthood. Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.

An edge-centric perspective on the human connectome: link communities in the brain.

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de Reus, Marcel A; Saenger, Victor M; Kahn, René S; van den Heuvel, Martijn P

2014-10-05

Brain function depends on efficient processing and integration of information within a complex network of neural interactions, known as the connectome. An important aspect of connectome architecture is the existence of community structure, providing an anatomical basis for the occurrence of functional specialization. Typically, communities are defined as groups of densely connected network nodes, representing clusters of brain regions. Looking at the connectome from a different perspective, instead focusing on the interconnecting links or edges, we find that the white matter pathways between brain regions also exhibit community structure. Eleven link communities were identified: five spanning through the midline fissure, three through the left hemisphere and three through the right hemisphere. We show that these link communities are consistently identifiable and investigate the network characteristics of their underlying white matter pathways. Furthermore, examination of the relationship between link communities and brain regions revealed that the majority of brain regions participate in multiple link communities. In particular, the highly connected and central hub regions showed a rich level of community participation, supporting the notion that these hubs play a pivotal role as confluence zones in which neural information from different domains merges. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder.

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Tiago Simas

Full Text Available The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric, such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric, where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC and major depressive disorder (MDD.Significance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome.These encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders.

Functional Brain Connectome and Its Relation to Hoehn and Yahr Stage in Parkinson Disease.

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Suo, Xueling; Lei, Du; Li, Nannan; Cheng, Lan; Chen, Fuqin; Wang, Meiyun; Kemp, Graham J; Peng, Rong; Gong, Qiyong

2017-12-01

Purpose To use resting-state functional magnetic resonance (MR) imaging and graph theory approaches to investigate the brain functional connectome and its potential relation to disease severity in Parkinson disease (PD). Materials and Methods This case-control study was approved by the local research ethics committee, and all participants provided informed consent. There were 153 right-handed patients with PD and 81 healthy control participants recruited who were matched for age, sex, and handedness to undergo a 3-T resting-state functional MR examination. The whole-brain functional connectome was constructed by thresholding the Pearson correlation matrices of 90 brain regions, and the topologic properties were analyzed by using graph theory approaches. Nonparametric permutation tests were used to compare topologic properties, and their relationship to disease severity was assessed. Results The functional connectome in PD showed abnormalities at the global level (ie, decrease in clustering coefficient, global efficiency, and local efficiency, and increase in characteristic path length) and at the nodal level (decreased nodal centralities in the sensorimotor cortex, default mode, and temporal-occipital regions; P left postcentral gyrus and left superior temporal gyrus correlated negatively with Unified Parkinson's Disease Rating Scale III score (P = .038, false discovery rate corrected, r = -0.198; and P = .009, false discovery rate corrected, r = -0.270, respectively) and decreased with increasing Hoehn and Yahr stage in patients with PD. Conclusion The configurations of brain functional connectome in patients with PD were perturbed and correlated with disease severity, notably with those responsible for motor functions. These results provide topologic insights into understanding the neural functional changes in relation to disease severity of PD. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article

Functional connectomics from a "big data" perspective.

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Xia, Mingrui; He, Yong

2017-10-15

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field. Copyright © 2017 Elsevier Inc. All rights reserved.

Stochastic Geometric Network Models for Groups of Functional and Structural Connectomes

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Friedman, Eric J.; Landsberg, Adam S.; Owen, Julia P.; Li, Yi-Ou; Mukherjee, Pratik

2014-01-01

Structural and functional connectomes are emerging as important instruments in the study of normal brain function and in the development of new biomarkers for a variety of brain disorders. In contrast to single-network studies that presently dominate the (non-connectome) network literature, connectome analyses typically examine groups of empirical networks and then compare these against standard (stochastic) network models. Current practice in connectome studies is to employ stochastic network models derived from social science and engineering contexts as the basis for the comparison. However, these are not necessarily best suited for the analysis of connectomes, which often contain groups of very closely related networks, such as occurs with a set of controls or a set of patients with a specific disorder. This paper studies important extensions of standard stochastic models that make them better adapted for analysis of connectomes, and develops new statistical fitting methodologies that account for inter-subject variations. The extensions explicitly incorporate geometric information about a network based on distances and inter/intra hemispherical asymmetries (to supplement ordinary degree-distribution information), and utilize a stochastic choice of networks' density levels (for fixed threshold networks) to better capture the variance in average connectivity among subjects. The new statistical tools introduced here allow one to compare groups of networks by matching both their average characteristics and the variations among them. A notable finding is that connectomes have high “smallworldness” beyond that arising from geometric and degree considerations alone. PMID:25067815

Connectomes as constitutively epistemic objects: Critical perspectives on modeling in current neuroanatomy.

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Haueis, Philipp; Slaby, Jan

2017-01-01

The term "connectome" is commonly taken to describe a complete map of neural connections in a nervous system of a given species. This chapter provides a critical perspective on the role of connectomes in neuroscientific practice and asks how the connectomic approach fits into a larger context in which network thinking permeates technology, infrastructure, social life, and the economy. In the first part of this chapter, we argue that, seen from the perspective of ongoing research, the notion of connectomes as "complete descriptions" is misguided. Our argument combines Rachel Ankeny's analysis of neuroanatomical wiring diagrams as "descriptive models" with Hans-Jörg Rheinberger's notion of "epistemic objects," i.e., targets of research that are still partially unknown. Combining these aspects we conclude that connectomes are constitutively epistemic objects: there just is no way to turn them into permanent and complete technical standards because the possibilities to map connection properties under different modeling assumptions are potentially inexhaustible. In the second part of the chapter, we use this understanding of connectomes as constitutively epistemic objects in order to critically assess the historical and political dimensions of current neuroscientific research. We argue that connectomics shows how the notion of the "brain as a network" has become the dominant metaphor of contemporary brain research. We further point out that this metaphor shares (potentially problematic) affinities to the form of contemporary "network societies." We close by pointing out how the relation between connectomes and networks in society could be used in a more fruitful manner. © 2017 Elsevier B.V. All rights reserved.

Brain enhancement through cognitive training: a new insight from brain connectome

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Fumihiko eTaya

2015-04-01

Full Text Available Owing to the recent advances in neurotechnology and the progress in understanding of brain cognitive functions, improvements of cognitive performance or acceleration of learning process with brain enhancement systems is not out of our reach anymore, on the contrary, it is a tangible target of contemporary research. Although a variety of approaches have been proposed, we will mainly focus on cognitive training interventions, in which learners repeatedly perform cognitive tasks to improve their cognitive abilities. In this review article, we propose that the learning process during the cognitive training can be facilitated by an assistive system monitoring cognitive workloads using EEG biomarkers, and the brain connectome approach can provide additional valuable biomarkers for facilitating leaners' learning processes. For the purpose, we will introduce studies on the cognitive training interventions, EEG biomarkers for cognitive workload, and human brain connectome. As cognitive overload and mental fatigue would reduce or even eliminate gains of cognitive training interventions, a real-time monitoring of cognitive workload can facilitate the learning process by flexibly adjusting difficulty levels of the training task. Moreover, cognitive training interventions should have effects on brain sub-networks, not on a single brain region, and graph theoretical network metrics quantifying topological architecture of the brain network can differentiate with respect to individual cognitive states as well as to different individuals' cognitive abilities, suggesting that the connectome is a valuable approach for tracking the learning progress. Although only a few studies have exploited the connectome approach for studying alterations of the brain network induced by cognitive training interventions so far, we believe that it would be a useful technique for capturing improvements of cognitive functions.

Brain enhancement through cognitive training: a new insight from brain connectome.

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Taya, Fumihiko; Sun, Yu; Babiloni, Fabio; Thakor, Nitish; Bezerianos, Anastasios

2015-01-01

Owing to the recent advances in neurotechnology and the progress in understanding of brain cognitive functions, improvements of cognitive performance or acceleration of learning process with brain enhancement systems is not out of our reach anymore, on the contrary, it is a tangible target of contemporary research. Although a variety of approaches have been proposed, we will mainly focus on cognitive training interventions, in which learners repeatedly perform cognitive tasks to improve their cognitive abilities. In this review article, we propose that the learning process during the cognitive training can be facilitated by an assistive system monitoring cognitive workloads using electroencephalography (EEG) biomarkers, and the brain connectome approach can provide additional valuable biomarkers for facilitating leaners' learning processes. For the purpose, we will introduce studies on the cognitive training interventions, EEG biomarkers for cognitive workload, and human brain connectome. As cognitive overload and mental fatigue would reduce or even eliminate gains of cognitive training interventions, a real-time monitoring of cognitive workload can facilitate the learning process by flexibly adjusting difficulty levels of the training task. Moreover, cognitive training interventions should have effects on brain sub-networks, not on a single brain region, and graph theoretical network metrics quantifying topological architecture of the brain network can differentiate with respect to individual cognitive states as well as to different individuals' cognitive abilities, suggesting that the connectome is a valuable approach for tracking the learning progress. Although only a few studies have exploited the connectome approach for studying alterations of the brain network induced by cognitive training interventions so far, we believe that it would be a useful technique for capturing improvements of cognitive functions.

A probabilistic atlas of human brainstem pathways based on connectome imaging data.

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Tang, Yuchun; Sun, Wei; Toga, Arthur W; Ringman, John M; Shi, Yonggang

2018-04-01

The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles

Connectome how the brain's wiring makes us who we are

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Seung, Sebastian

2012-01-01

Connectome, by Sebastian Seung is 'One of the most eagerly awaited scientific books of the year ... intellectually exhilarating, beautifully written, exquisitely precise yet still managing to be inspirational' Irish Times What really makes us who we are? In this groundbreaking book, pioneering neuroscientist Sebastian Seung shows that our identity does not lie in our genes, but in the connections between our brain cells - our own particular wiring, or 'connectomes'.Everything about us - emotions, thoughts, memories - is encoded in these tangled patterns of neural connections, and now Seung and a dedicated team are mapping them in order to uncover the basis of personality, explain disorders such as autism and depression, and even enable us to 'upload' our brains. This book reveals the secrets of the brain, showing how our connectome makes each of us uniquely ourselves. 'With the first-person flavour of James Watson's Double Helix, Connectome gives a sense of the excitement on the cutting edge of neuroscience' ...

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

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Jahanshad, Neda; Rajagopalan, Priya; Hua, Xue; Hibar, Derrek P.; Nir, Talia M.; Toga, Arthur W.; Jack, Clifford R.; Saykin, Andrew J.; Green, Robert C.; Weiner, Michael W.; Medland, Sarah E.; Montgomery, Grant W.; Hansell, Narelle K.; McMahon, Katie L.; de Zubicaray, Greig I.; Martin, Nicholas G.; Wright, Margaret J.; Thompson, Paul M.; Weiner, Michael; Aisen, Paul; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowski, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Liu, Enchi; Green, Robert C.; Montine, Tom; Petersen, Ronald; Aisen, Paul; Gamst, Anthony; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Gessert, Devon; Sather, Tamie; Beckett, Laurel; Harvey, Danielle; Gamst, Anthony; Donohue, Michael; Kornak, John; Jack, Clifford R.; Dale, Anders; Bernstein, Matthew; Felmlee, Joel; Fox, Nick; Thompson, Paul; Schuff, Norbert; Alexander, Gene; DeCarli, Charles; Jagust, William; Bandy, Dan; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Mathis, Chet; Morris, John; Cairns, Nigel J.; Taylor-Reinwald, Lisa; Trojanowki, J.Q.; Shaw, Les; Lee, Virginia M.Y.; Korecka, Magdalena; Toga, Arthur W.; Crawford, Karen; Neu, Scott; Saykin, Andrew J.; Foroud, Tatiana M.; Potkin, Steven; Shen, Li; Khachaturian, Zaven; Frank, Richard; Snyder, Peter J.; Molchan, Susan; Kaye, Jeffrey; Quinn, Joseph; Lind, Betty; Dolen, Sara; Schneider, Lon S.; Pawluczyk, Sonia; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Heidebrink, Judith L.; Lord, Joanne L.; Petersen, Ronald; Johnson, Kris; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Morris, John C.; Ances, Beau; Carroll, Maria; Leon, Sue; Mintun, Mark A.; Schneider, Stacy; Marson, Daniel; Griffith, Randall; Clark, David; Grossman, Hillel; Mitsis, Effie; Romirowsky, Aliza; deToledo-Morrell, Leyla; Shah, Raj C.; Duara, Ranjan; Varon, Daniel; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; Kielb, Stephanie; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; De Santi, Susan; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Coleman, R. Edward; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Lopez, Oscar L.; Oakley, MaryAnn; Simpson, Donna M.; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Diaz-Arrastia, Ramon; King, Richard; Weiner, Myron; Martin-Cook, Kristen; DeVous, Michael; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Anderson, Heather S.; Swerdlow, Russell H.; Apostolova, Liana; Lu, Po H.; Bartzokis, George; Silverman, Daniel H.S.; Graff-Radford, Neill R.; Parfitt, Francine; Johnson, Heather; Farlow, Martin R.; Hake, Ann Marie; Matthews, Brandy R.; Herring, Scott; van Dyck, Christopher H.; Carson, Richard E.; MacAvoy, Martha G.; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Hsiung, Ging-Yuek Robin; Feldman, Howard; Mudge, Benita; Assaly, Michele; Kertesz, Andrew; Rogers, John; Trost, Dick; Bernick, Charles; Munic, Donna; Kerwin, Diana; Mesulam, Marek-Marsel; Lipowski, Kristina; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Martinez, Walter; Villena, Teresa; Turner, Raymond Scott; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Frey, Meghan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan; Belden, Christine; Jacobson, Sandra; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Obisesan, Thomas O.; Wolday, Saba; Bwayo, Salome K.; Lerner, Alan; Hudson, Leon; Ogrocki, Paula; Fletcher, Evan; Carmichael, Owen; Olichney, John; DeCarli, Charles; Kittur, Smita; Borrie, Michael; Lee, T.-Y.; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Potkin, Steven G.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Saykin, Andrew J.; Santulli, Robert B.; Schwartz, Eben S.; Sink, Kaycee M.; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Mintzer, Jacobo; Longmire, Crystal Flynn; Spicer, Kenneth; Finger, Elizabeth; Rachinsky, Irina; Rogers, John; Kertesz, Andrew; Drost, Dick

2013-01-01

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases. PMID:23471985

Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD.

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Atasoy, Selen; Roseman, Leor; Kaelen, Mendel; Kringelbach, Morten L; Deco, Gustavo; Carhart-Harris, Robin L

2017-12-15

Recent studies have started to elucidate the effects of lysergic acid diethylamide (LSD) on the human brain but the underlying dynamics are not yet fully understood. Here we used 'connectome-harmonic decomposition', a novel method to investigate the dynamical changes in brain states. We found that LSD alters the energy and the power of individual harmonic brain states in a frequency-selective manner. Remarkably, this leads to an expansion of the repertoire of active brain states, suggestive of a general re-organization of brain dynamics given the non-random increase in co-activation across frequencies. Interestingly, the frequency distribution of the active repertoire of brain states under LSD closely follows power-laws indicating a re-organization of the dynamics at the edge of criticality. Beyond the present findings, these methods open up for a better understanding of the complex brain dynamics in health and disease.

Consciousness, Plasticity, and Connectomics: The Role of Intersubjectivity in Human Cognition

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Micah eAllen

2011-02-01

Full Text Available Consciousness is typically construed as being explainable purely in terms of either private, raw feels or higher-order, reflective representations. In contrast to this false dichotomy, we propose a new view of consciousness as an interactive, plastic phenomenon open to sociocultural influence. We take up our account of consciousness from the observation of radical cortical neuroplasticity in human development. Accordingly, we draw upon recent research on macroscopic neural networks, including the default mode, to illustrate cases in which an individual’s particular connectome is shaped by encultured social practices that depend upon and influence phenomenal and reflective consciousness. On our account, the dynamically interacting connectivity of these networks bring about important individual differences in conscious experience and determine what is present in consciousness. Further, we argue that the organization of the brain into discrete anti-correlated networks supports the phenomenological distinction of prereflective and reflective consciousness, but we emphasize that this finding must be interpreted in light of the dynamic, category-resistant nature of consciousness. Our account motivates philosophical and empirical hypotheses regarding the appropriate time-scale and function of neuroplastic adaptation, the relation of high and low frequency neural activity to consciousness and cognitive plasticity, and the role of ritual social practices in neural development and cognitive function.

In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI.

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Bianciardi, Marta; Toschi, Nicola; Eichner, Cornelius; Polimeni, Jonathan R; Setsompop, Kawin; Brown, Emery N; Hämäläinen, Matti S; Rosen, Bruce R; Wald, Lawrence L

2016-06-01

Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data. We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s). The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work. Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.

Heritability of the human connectome: A connectotyping study

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Oscar Miranda-Dominguez

2018-06-01

Full Text Available Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks. By using machine learning and two independent datasets, this report shows that the brain’s individualized functional connectome or connectotype is familial and heritable. First we expand previous findings showing that by using a model-based approach to characterize functional connectivity, we can reliably identify and track individual brain signatures—a functional “fingerprint” or “connectotype” for the human brain—in both children and adults. Such signatures can also be used to characterize familial and heritable patterns of brain connectivity, even using limited data. Most heritable systems include the fronto-parietal, dorsal attention, ventral attention

From cosmos to connectomes: the evolution of data-intensive science.

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Burns, Randal; Vogelstein, Joshua T; Szalay, Alexander S

2014-09-17

The analysis of data requires computation: originally by hand and more recently by computers. Different models of computing are designed and optimized for different kinds of data. In data-intensive science, the scale and complexity of data exceeds the comfort zone of local data stores on scientific workstations. Thus, cloud computing emerges as the preeminent model, utilizing data centers and high-performance clusters, enabling remote users to access and query subsets of the data efficiently. We examine how data-intensive computational systems originally built for cosmology, the Sloan Digital Sky Survey (SDSS), are now being used in connectomics, at the Open Connectome Project. We list lessons learned and outline the top challenges we expect to face. Success in computational connectomics would drastically reduce the time between idea and discovery, as SDSS did in cosmology. Copyright © 2014 Elsevier Inc. All rights reserved.

Changes in functional organization and white matter integrity in the connectome in Parkinson's disease

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Sule Tinaz

2017-01-01

Our results suggest that despite subtle white matter connectivity changes, the overall structural organization of the PD connectome remains robust at relatively early disease stages. However, there is a breakdown in the functional modular organization of the PD connectome.

EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome.

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Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; El Falou, Wassim; Wendling, Fabrice

2015-01-01

The brain is a large-scale complex network often referred to as the "connectome". Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/.

Statistical methods and challenges in connectome genetics

KAUST Repository

Pluta, Dustin; Yu, Zhaoxia; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando

2018-01-01

The study of genetic influences on brain connectivity, known as connectome genetics, is an exciting new direction of research in imaging genetics. We here review recent results and current statistical methods in this area, and discuss some

Editorial: New Trends in Connectomics

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Olaf Sporns

2018-06-01

Full Text Available Connectomics is an integral part of network neuroscience. The field has undergone rapid expansion over recent years and increasingly involves a blend of experimental and computational approaches to brain connectivity. This Focus Feature on “New Trends in Connectomics” aims to track the progress of the field and its many applications across different neurobiological systems and species.

Globally Efficient Brain Organization and Treatment Response in Psychosis: A Connectomic Study of Gyrification.

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Palaniyappan, Lena; Marques, Tiago Reis; Taylor, Heather; Mondelli, Valeria; Reinders, A A T Simone; Bonaccorso, Stefania; Giordano, Annalisa; DiForti, Marta; Simmons, Andrew; David, Anthony S; Pariante, Carmine M; Murray, Robin M; Dazzan, Paola

2016-11-01

Converging evidence suggests that patients with first-episode psychosis who show a poor treatment response may have a higher degree of neurodevelopmental abnormalities than good Responders. Characterizing the disturbances in the relationship among brain regions (covariance) can provide more information on neurodevelopmental integrity than searching for localized changes in the brain. Graph-based connectomic approach can measure structural covariance thus providing information on the maturational processes. We quantified the structural covariance of cortical folding using graph theory in first-episode psychosis, to investigate if this systems-level approach would improve our understanding of the biological determinants of outcome in psychosis. Magnetic Resonance Imaging data were acquired in 80 first-episode psychosis patients and 46 healthy controls. Response to treatment was assessed after 12 weeks of naturalistic follow-up. Gyrification-based connectomes were constructed to study the maturational organization of cortical folding. Nonresponders showed a reduction in the distributed relationship among brain regions (high segregation, poor integration) when compared to Responders and controls, indicating a higher burden of aberrant neurodevelopment. They also showed reduced centrality of key regions (left insula and anterior cingulate cortex) indicating a marked reconfiguration of gyrification. Nonresponders showed a vulnerable pattern of covariance that disintegrated when simulated lesions removed high-degree hubs, indicating an abnormal dependence on highly central hub regions in Nonresponders. These findings suggest that a perturbed maturational relationship among brain regions underlies poor treatment response in first-episode psychosis. The information obtained from gyrification-based connectomes can be harnessed for prospectively predicting treatment response and prognosis in psychosis. © The Author 2016. Published by Oxford University Press on behalf of the

Estimating the impact of structural directionality: How reliable are undirected connectomes?

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Penelope Kale

2018-06-01

Full Text Available Directionality is a fundamental feature of network connections. Most structural brain networks are intrinsically directed because of the nature of chemical synapses, which comprise most neuronal connections. Because of the limitations of noninvasive imaging techniques, the directionality of connections between structurally connected regions of the human brain cannot be confirmed. Hence, connections are represented as undirected, and it is still unknown how this lack of directionality affects brain network topology. Using six directed brain networks from different species and parcellations (cat, mouse, C. elegans, and three macaque networks, we estimate the inaccuracies in network measures (degree, betweenness, clustering coefficient, path length, global efficiency, participation index, and small-worldness associated with the removal of the directionality of connections. We employ three different methods to render directed brain networks undirected: (a remove unidirectional connections, (b add reciprocal connections, and (c combine equal numbers of removed and added unidirectional connections. We quantify the extent of inaccuracy in network measures introduced through neglecting connection directionality for individual nodes and across the network. We find that the coarse division between core and peripheral nodes remains accurate for undirected networks. However, hub nodes differ considerably when directionality is neglected. Comparing the different methods to generate undirected networks from directed ones, we generally find that the addition of reciprocal connections (false positives causes larger errors in graph-theoretic measures than the removal of the same number of directed connections (false negatives. These findings suggest that directionality plays an essential role in shaping brain networks and highlight some limitations of undirected connectomes. Most brain networks are inherently directed because of the nature of chemical synapses

Diffusion tensor imaging using multiple coils for mouse brain connectomics.

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Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G

2018-04-19

The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity

The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.

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Howell, Brittany R; Styner, Martin A; Gao, Wei; Yap, Pew-Thian; Wang, Li; Baluyot, Kristine; Yacoub, Essa; Chen, Geng; Potts, Taylor; Salzwedel, Andrew; Li, Gang; Gilmore, John H; Piven, Joseph; Smith, J Keith; Shen, Dinggang; Ugurbil, Kamil; Zhu, Hongtu; Lin, Weili; Elison, Jed T

2018-03-22

The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain-behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high-resolution structural MRI (T1-and T2-weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0-5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well-established behavioral assessments during this time period will yield an invaluable resource for the scientific community. Copyright © 2018 Elsevier Inc. All rights reserved.

Statistical methods and challenges in connectome genetics

KAUST Repository

Pluta, Dustin

2018-03-12

The study of genetic influences on brain connectivity, known as connectome genetics, is an exciting new direction of research in imaging genetics. We here review recent results and current statistical methods in this area, and discuss some of the persistent challenges and possible directions for future work.

Compresso: Efficient Compression of Segmentation Data for Connectomics

KAUST Repository

Matejek, Brian; Haehn, Daniel; Lekschas, Fritz; Mitzenmacher, Michael; Pfister, Hanspeter

2017-01-01

Recent advances in segmentation methods for connectomics and biomedical imaging produce very large datasets with labels that assign object classes to image pixels. The resulting label volumes are bigger than the raw image data and need compression

Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain

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Mingrui eXia

2016-04-01

Full Text Available White matter (WM tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption and topological contributions to the brain’s network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain’s hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivity

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Giancardo, Luca; Ellmore, Timothy M.; Suescun, Jessika; Ocasio, Laura; Kamali, Arash; Riascos-Castaneda, Roy; Schiess, Mya C.

2018-02-01

Methods to identify neuroplasticity patterns in human brains are of the utmost importance in understanding and potentially treating neurodegenerative diseases. Parkinson disease (PD) research will greatly benefit and advance from the discovery of biomarkers to quantify brain changes in the early stages of the disease, a prodromal period when subjects show no obvious clinical symptoms. Diffusion tensor imaging (DTI) allows for an in-vivo estimation of the structural connectome inside the brain and may serve to quantify the degenerative process before the appearance of clinical symptoms. In this work, we introduce a novel strategy to compute longitudinal structural connectomes in the context of a whole-brain data-driven pipeline. In these initial tests, we show that our predictive models are able to distinguish controls from asymptomatic subjects at high risk of developing PD (REM sleep behavior disorder, RBD) with an area under the receiving operating characteristic curve of 0.90 (pParkinson's Progression Markers Initiative. By analyzing the brain connections most relevant for the predictive ability of the best performing model, we find connections that are biologically relevant to the disease.

Neuroplasticity and the brain connectome: what can Jean Talairach's reflections bring to modern psychosurgery?

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Bourdillon, Pierre; Apra, Caroline; Lévêque, Marc; Vinckier, Fabien

2017-09-01

Contrary to common psychosurgical practice in the 1950s, Dr. Jean Talairach had the intuition, based on clinical experience, that the brain connectome and neuroplasticity had a role to play in psychosurgery. Due to the remarkable progress of pharmacology at that time and to the technical limits of neurosurgery, these concepts were not put into practice. Currently, these concepts are being confirmed by modern techniques such as neuroimaging and computational neurosciences, and could pave the way for therapeutic innovation in psychiatry. Psychosurgery commonly uses a localizationist approach, based on the idea that a lesion to a specific area is responsible for a deficit opposite to its function. To psychosurgeons such as Walter Freeman, who performed extensive lesions causing apparently inevitable deficit, Talairach answered with clinical data: complex psychic functions cannot be described that simply, because the same lesion does not provoke the same deficit in different patients. Moreover, cognitive impairment did not always follow efficacious psychosurgery. Talairach suggested that selectively destructing part of a network could open the door to a new organization, and that early psychotherapy could encourage this psychoplasticity. Talairach did not have the opportunity to put these concepts into practice in psychiatric diseases because of the sudden availability of neuroleptics, but connectomics and neuroplasticity gave rise to major advances in intraparenchymal neurosurgery, from epilepsy to low-grade glioma. In psychiatry, alongside long-standing theories implicating focal lesions and diffuse pathological processes, neuroimaging techniques are currently being developed. In mentally healthy individuals, combining diffusion tensor imaging with functional MRI, magnetoencephalography, and electroencephalography allows the determination of a comprehensive map of neural connections in the brain on many spatial scales, the so-called connectome. Ultimately, global

Multimodal neural correlates of cognitive control in the Human Connectome Project.

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Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions

Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery.

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Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John

2016-06-01

Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

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Bastiani, Matteo; Andersson, Jesper L R; Cordero-Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N; Makropoulos, Antonios; Fitzgibbon, Sean P; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A David; Smith, Stephen M; Tournier, Jacques-Donald; Hajnal, Joseph V; Jbabdi, Saad; Sotiropoulos, Stamatios N

2018-05-28

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Communication and Wiring in the Cortical Connectome

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Julian eBudd

2012-10-01

Full Text Available In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimise communication there is a trade-off between spatial (construction and temporal (routing costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fibre tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for

Connectome-scale group-wise consistent resting-state network analysis in autism spectrum disorder

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Yu Zhao

2016-01-01

Full Text Available Understanding the organizational architecture of human brain function and its alteration patterns in diseased brains such as Autism Spectrum Disorder (ASD patients are of great interests. In-vivo functional magnetic resonance imaging (fMRI offers a unique window to investigate the mechanism of brain function and to identify functional network components of the human brain. Previously, we have shown that multiple concurrent functional networks can be derived from fMRI signals using whole-brain sparse representation. Yet it is still an open question to derive group-wise consistent networks featured in ASD patients and controls. Here we proposed an effective volumetric network descriptor, named connectivity map, to compactly describe spatial patterns of brain network maps and implemented a fast framework in Apache Spark environment that can effectively identify group-wise consistent networks in big fMRI dataset. Our experiment results identified 144 group-wisely common intrinsic connectivity networks (ICNs shared between ASD patients and healthy control subjects, where some ICNs are substantially different between the two groups. Moreover, further analysis on the functional connectivity and spatial overlap between these 144 common ICNs reveals connectomics signatures characterizing ASD patients and controls. In particular, the computing time of our Spark-enabled functional connectomics framework is significantly reduced from 240 hours (C++ code, single core to 20 hours, exhibiting a great potential to handle fMRI big data in the future.

Flow-Based Network Analysis of the Caenorhabditis elegans Connectome.

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Bacik, Karol A; Schaub, Michael T; Beguerisse-Díaz, Mariano; Billeh, Yazan N; Barahona, Mauricio

2016-08-01

We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios.

Investigating the capability to resolve complex white matter structures with high b-value diffusion magnetic resonance imaging on the MGH-USC Connectom scanner.

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Fan, Qiuyun; Nummenmaa, Aapo; Witzel, Thomas; Zanzonico, Roberta; Keil, Boris; Cauley, Stephen; Polimeni, Jonathan R; Tisdall, Dylan; Van Dijk, Koene R A; Buckner, Randy L; Wedeen, Van J; Rosen, Bruce R; Wald, Lawrence L

2014-11-01

One of the major goals of the NIH Blueprint Human Connectome Project was to map and quantify the white matter connections in the brain using diffusion tractography. Given the prevalence of complex white matter structures, the capability of resolving local white matter geometries with multiple crossings in the diffusion magnetic resonance imaging (dMRI) data is critical. Increasing b-value has been suggested for delineation of the finer details of the orientation distribution function (ODF). Although increased gradient strength and duration increase sensitivity to highly restricted intra-axonal water, gradient strength limitations require longer echo times (TE) to accommodate the increased diffusion encoding times needed to achieve a higher b-value, exponentially lowering the signal-to-noise ratio of the acquisition. To mitigate this effect, the MGH-USC Connectom scanner was built with 300 mT/m gradients, which can significantly reduce the TE of high b-value diffusion imaging. Here we report comparisons performed across b-values based on q-ball ODF metrics to investigate whether high b-value diffusion imaging on the Connectom scanner can improve resolving complex white matter structures. The q-ball ODF features became sharper as the b-value increased, with increased power fraction in higher order spherical harmonic series of the ODF and increased peak heights relative to the overall size of the ODF. Crossing structures were detected in an increasingly larger fraction of white matter voxels and the spatial distribution of two-way and three-way crossing structures was largely consistent with known anatomy. Results indicate that dMRI with high diffusion encoding on the Connectom system is a promising tool to better characterize, and ultimately understand, the underlying structural organization and motifs in the human brain.

Connectomic disturbances in attention-deficit/hyperactivity disorder: a whole-brain tractography analysis.

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Hong, Soon-Beom; Zalesky, Andrew; Fornito, Alex; Park, Subin; Yang, Young-Hui; Park, Min-Hyeon; Song, In-Chan; Sohn, Chul-Ho; Shin, Min-Sup; Kim, Bung-Nyun; Cho, Soo-Churl; Han, Doug Hyun; Cheong, Jae Hoon; Kim, Jae-Won

2014-10-15

Few studies have sought to identify, in a regionally unbiased way, the precise cortical and subcortical regions that are affected by white matter abnormalities in attention-deficit/hyperactivity disorder (ADHD). This study aimed to derive a comprehensive, whole-brain characterization of connectomic disturbances in ADHD. Using diffusion tensor imaging, whole-brain tractography, and an imaging connectomics approach, we characterized altered white matter connectivity in 71 children and adolescents with ADHD compared with 26 healthy control subjects. White matter differences were further delineated between patients with (n = 40) and without (n = 26) the predominantly hyperactive/impulsive subtype of ADHD. A significant network comprising 25 distinct fiber bundles linking 23 different brain regions spanning frontal, striatal, and cerebellar brain regions showed altered white matter structure in ADHD patients (p attentional disturbances. Attention-deficit/hyperactivity disorder subtypes were differentiated by a right-lateralized network (p attentional performance underscore the functional importance of these connectomic disturbances for the clinical phenotype of ADHD. A distributed pattern of white matter microstructural integrity separately involving frontal, striatal, and cerebellar brain regions, rather than direct frontostriatal connectivity, appears to be disrupted in children and adolescents with ADHD. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Asymmetry of the structural brain connectome in healthy older adults.

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Leonardo eBonilha

2014-01-01

Full Text Available Background: It is now possible to map neural connections in vivo across the whole brain (i.e., the brain connectome. This is a promising development in neuroscience since many health and disease processes are believed to arise from the architecture of neural networks.Objective: To describe the normal range of hemispheric asymmetry in structural connectivity in healthy older adults.Methods: We obtained high-resolution structural magnetic resonance images (MRI from 17 healthy older adults. For each subject, the brain connectome was reconstructed by parcelating the probabilistic map of gray matter into anatomically defined regions of interested (ROIs. White matter fiber tractography was reconstructed from diffusion tensor imaging and streamlines connecting gray matter ROIs were computed. Asymmetry indices were calculated regarding ROI connectivity (representing the sum of connectivity weight of each cortical ROI and for regional white matter links. All asymmetry measures were compared to a normal distribution with mean=0 through one sample t-tests.Results: Leftward cortical ROI asymmetry was observed in medial temporal, dorsolateral frontal and occipital regions. Rightward cortical ROI asymmetry was observed in middle temporal and orbito-frontal regions. Link-wise asymmetry revealed stronger connections in the left hemisphere between the medial temporal, anterior and posterior peri-Sylvian and occipito-temporal regions. Rightward link asymmetry was observed in lateral temporal, parietal and dorsolateral frontal connections.Conclusions: We postulate that asymmetry of specific connections may be related to functional hemispheric organization. This study may provide reference for future studies evaluating the architecture of the connectome in health and disease processes in senior individuals.

Using high-throughput barcode sequencing to efficiently map connectomes.

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Peikon, Ian D; Kebschull, Justus M; Vagin, Vasily V; Ravens, Diana I; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R; Bressan, Dario; Zador, Anthony M

2017-07-07

The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Network control principles predict neuron function in the Caenorhabditis elegans connectome

Science.gov (United States)

Yan, Gang; Vértes, Petra E.; Towlson, Emma K.; Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László

2017-10-01

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

Network control principles predict neuron function in the Caenorhabditis elegans connectome.

Science.gov (United States)

Yan, Gang; Vértes, Petra E; Towlson, Emma K; Chew, Yee Lian; Walker, Denise S; Schafer, William R; Barabási, Albert-László

2017-10-26

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

Introducing axonal myelination in connectomics: A preliminary analysis of g-ratio distribution in healthy subjects.

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Mancini, Matteo; Giulietti, Giovanni; Dowell, Nicholas; Spanò, Barbara; Harrison, Neil; Bozzali, Marco; Cercignani, Mara

2017-09-14

Microstructural imaging and connectomics are two research areas that hold great potential for investigating brain structure and function. Combining these two approaches can lead to a better and more complete characterization of the brain as a network. The aim of this work is characterizing the connectome from a novel perspective using the myelination measure given by the g-ratio. The g-ratio is the ratio of the inner to the outer diameters of a myelinated axon, whose aggregated value can now be estimated in vivo using MRI. In two different datasets of healthy subjects, we reconstructed the structural connectome and then used the g-ratio estimated from diffusion and magnetization transfer data to characterize the network structure. Significant characteristics of g-ratio weighted graphs emerged. First, the g-ratio distribution across the edges of the graph did not show the power-law distribution observed using the number of streamlines as a weight. Second, connections involving regions related to motor and sensory functions were the highest in myelin content. We also observed significant differences in terms of the hub structure and the rich-club organization suggesting that connections involving hub regions present higher myelination than peripheral connections. Taken together, these findings offer a characterization of g-ratio distribution across the connectome in healthy subjects and lay the foundations for further investigating plasticity and pathology using a similar approach. Copyright © 2017. Published by Elsevier Inc.

Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

Science.gov (United States)

Markett, Sebastian; Reuter, Martin; Heeren, Behrend; Lachmann, Bernd; Weber, Bernd; Montag, Christian

2018-02-01

The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.

Science.gov (United States)

Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong

2014-12-01

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.

Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

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Yiming Fan

2017-09-01

Full Text Available Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying functional connectivity patterns of the developing and aging brain. Normal brain development is characterized by continuous and significant network evolution through infancy, childhood, and adolescence, following specific maturational patterns. Normal aging is related to some resting state brain networks disruption, which are associated with certain cognitive decline. It is a big challenge to design an integral metric to track connectome evolution patterns across the lifespan, which is to understand the principles of network organization in the human brain. In this study, we first defined a brain network eigen-entropy (NEE based on the energy probability (EP of each brain node. Next, we used the NEE to characterize the lifespan orderness trajectory of the whole-brain functional connectivity of 173 healthy individuals ranging in age from 7 to 85 years. The results revealed that during the lifespan, the whole-brain NEE exhibited a significant non-linear decrease and that the EP distribution shifted from concentration to wide dispersion, implying orderness enhancement of functional connectome over age. Furthermore, brain regions with significant EP changes from the flourishing (7–20 years to the youth period (23–38 years were mainly located in the right prefrontal cortex and basal ganglia, and were involved in emotion regulation and executive function in coordination with the action of the sensory system, implying that self-awareness and voluntary control performance significantly changed during neurodevelopment. However, the changes from the youth period to middle age (40–59 years were located in the mesial temporal lobe and caudate, which are associated with long-term memory, implying that the memory of the human brain begins to decline with age during this period. Overall, the findings suggested that the human connectome

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

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Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C; Zhou, Changsong

2017-09-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may

Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads.

Science.gov (United States)

Lee, Tae-Ho; Miernicki, Michelle E; Telzer, Eva H

2017-05-15

Despite emerging evidence suggesting a biological basis to our social tiles, our understanding of the neural processes which link two minds is unknown. We implemented a novel approach, which included connectome similarity analysis using resting state intrinsic networks of parent-child dyads as well as daily diaries measured across 14 days. Intrinsic resting-state networks for both parents and their adolescent child were identified using independent component analysis (ICA). Results indicate that parents and children who had more similar RSN connectome also had more similar day-to-day emotional synchrony. Furthermore, dyadic RSN connectome similarity was associated with children's emotional competence, suggesting that being neurally in-tune with their parents confers emotional benefits. We provide the first evidence that dyadic RSN similarity is associated with emotional synchrony in what is often our first and most essential social bond, the parent-child relationship. Copyright © 2017 Elsevier Inc. All rights reserved.

From a meso- to micro-scale connectome: Array Tomography and mGRASP

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Jinhyun eKim

2015-06-01

Full Text Available Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing, combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors.

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

Science.gov (United States)

Finn, Emily S; Shen, Xilin; Scheinost, Dustin; Rosenberg, Monica D; Huang, Jessica; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

2015-11-01

Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.

Brain without anatomy: construction and comparison of fully network-driven structural MRI connectomes.

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Olga Tymofiyeva

Full Text Available MRI connectomics methods treat the brain as a network and provide new information about its organization, efficiency, and mechanisms of disruption. The most commonly used method of defining network nodes is to register the brain to a standardized anatomical atlas based on the Brodmann areas. This approach is limited by inter-subject variability and can be especially problematic in the context of brain maturation or neuroplasticity (cerebral reorganization after brain damage. In this study, we combined different image processing and network theory methods and created a novel approach that enables atlas-free construction and connection-wise comparison of diffusion MRI-based brain networks. We illustrated the proposed approach in three age groups: neonates, 6-month-old infants, and adults. First, we explored a data-driven method of determining the optimal number of equal-area nodes based on the assumption that all cortical areas of the brain are connected and, thus, no part of the brain is structurally isolated. Second, to enable a connection-wise comparison, alignment to a "reference brain" was performed in the network domain within each group using a matrix alignment algorithm with simulated annealing. The correlation coefficients after pair-wise network alignment ranged from 0.6102 to 0.6673. To test the method's reproducibility, one subject from the 6-month-old group and one from the adult group were scanned twice, resulting in correlation coefficients of 0.7443 and 0.7037, respectively. While being less than 1 due to parcellation and noise, statistically, these values were significantly higher than inter-subject values. Rotation of the parcellation largely explained the variability. Through the abstraction from anatomy, the developed framework allows for a fully network-driven analysis of structural MRI connectomes and can be applied to subjects at any stage of development and with substantial differences in cortical anatomy.

The application of a mathematical model linking structural and functional connectomes in severe brain injury

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A. Kuceyeski

2016-01-01

Full Text Available Following severe injuries that result in disorders of consciousness, recovery can occur over many months or years post-injury. While post-injury synaptogenesis, axonal sprouting and functional reorganization are known to occur, the network-level processes underlying recovery are poorly understood. Here, we test a network-level functional rerouting hypothesis in recovery of patients with disorders of consciousness following severe brain injury. This hypothesis states that the brain recovers from injury by restoring normal functional connections via alternate structural pathways that circumvent impaired white matter connections. The so-called network diffusion model, which relates an individual's structural and functional connectomes by assuming that functional activation diffuses along structural pathways, is used here to capture this functional rerouting. We jointly examined functional and structural connectomes extracted from MRIs of 12 healthy and 16 brain-injured subjects. Connectome properties were quantified via graph theoretic measures and network diffusion model parameters. While a few graph metrics showed groupwise differences, they did not correlate with patients' level of consciousness as measured by the Coma Recovery Scale — Revised. There was, however, a strong and significant partial Pearson's correlation (accounting for age and years post-injury between level of consciousness and network diffusion model propagation time (r = 0.76, p < 0.05, corrected, i.e. the time functional activation spends traversing the structural network. We concluded that functional rerouting via alternate (and less efficient pathways leads to increases in network diffusion model propagation time. Simulations of injury and recovery in healthy connectomes confirmed these results. This work establishes the feasibility for using the network diffusion model to capture network-level mechanisms in recovery of consciousness after severe brain injury.

The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles.

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Aharon Azulay

2016-09-01

Full Text Available A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available.

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

Directory of Open Access Journals (Sweden)

Yuhan Chen

2017-09-01

Full Text Available The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56% explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs. The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially

Atypical Structural Connectome Organization and Cognitive Impairment in Young Survivors of Acute Lymphoblastic Leukemia.

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Kesler, Shelli R; Gugel, Meike; Huston-Warren, Emily; Watson, Christa

2016-05-01

Survivors of pediatric acute lymphoblastic leukemia (ALL) are at increased risk for cognitive impairments that disrupt everyday functioning and decrease quality of life. The specific biological mechanisms underlying cognitive impairment following ALL remain largely unclear, but previous studies consistently demonstrate significant white matter pathology. We aimed to extend this literature by examining the organization of the white matter connectome in young patients with a history of ALL treated with chemotherapy only. We applied graph theoretical analysis to diffusion tensor imaging obtained from 31 survivors of ALL age 5-19 years and 39 matched healthy controls. Results indicated significantly lower small-worldness (p = 0.007) and network clustering coefficient (p = 0.019), as well as greater cognitive impairment (p = 0.027) in the ALL group. Regional analysis indicated that clustered connectivity in parietal, frontal, hippocampal, amygdalar, thalamic, and occipital regions was altered in the ALL group. Random forest analysis revealed a model of connectome and demographic variables that could automatically classify survivors of ALL as having cognitive impairment or not (accuracy = 0.89, p < 0.0001). These findings provide further evidence of brain injury in young survivors of ALL, even those without a history of central nervous system (CNS) disease or cranial radiation. Efficiency of local information processing, reorganization of hub connectivity, and cognitive reserve may contribute to cognitive outcome in these children. Certain connectome properties showed U-shaped relationships with cognitive impairment suggesting an optimal range of regional connectivity.

ConnectomeExplorer: Query-guided visual analysis of large volumetric neuroscience data

KAUST Repository

Beyer, Johanna

2013-12-01

This paper presents ConnectomeExplorer, an application for the interactive exploration and query-guided visual analysis of large volumetric electron microscopy (EM) data sets in connectomics research. Our system incorporates a knowledge-based query algebra that supports the interactive specification of dynamically evaluated queries, which enable neuroscientists to pose and answer domain-specific questions in an intuitive manner. Queries are built step by step in a visual query builder, building more complex queries from combinations of simpler queries. Our application is based on a scalable volume visualization framework that scales to multiple volumes of several teravoxels each, enabling the concurrent visualization and querying of the original EM volume, additional segmentation volumes, neuronal connectivity, and additional meta data comprising a variety of neuronal data attributes. We evaluate our application on a data set of roughly one terabyte of EM data and 750 GB of segmentation data, containing over 4,000 segmented structures and 1,000 synapses. We demonstrate typical use-case scenarios of our collaborators in neuroscience, where our system has enabled them to answer specific scientific questions using interactive querying and analysis on the full-size data for the first time. © 1995-2012 IEEE.

Abnormal wiring of the connectome in adults with high-functioning autism spectrum disorder

OpenAIRE

Roine, Ulrika; Roine, Timo; Salmi, Juha; Nieminen-von Wendt, Taina; Tani, Pekka; Lepp?m?ki, Sami; Rintahaka, Pertti; Caeyenberghs, Karen; Leemans, Alexander; Sams, Mikko

2015-01-01

Abstract Background Recent brain imaging findings suggest that there are widely distributed abnormalities affecting the brain connectivity in individuals with autism spectrum disorder (ASD). Using graph theoretical analysis, it is possible to investigate both global and local properties of brain’s wiring diagram, i.e., the connectome. Methods We acquired diffusion-...

Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.

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Eduardo J Izquierdo

Full Text Available Increased efforts in the assembly and analysis of connectome data are providing new insights into the principles underlying the connectivity of neural circuits. However, despite these considerable advances in connectomics, neuroanatomical data must be integrated with neurophysiological and behavioral data in order to obtain a complete picture of neural function. Due to its nearly complete wiring diagram and large behavioral repertoire, the nematode worm Caenorhaditis elegans is an ideal organism in which to explore in detail this link between neural connectivity and behavior. In this paper, we develop a neuroanatomically-grounded model of salt klinotaxis, a form of chemotaxis in which changes in orientation are directed towards the source through gradual continual adjustments. We identify a minimal klinotaxis circuit by systematically searching the C. elegans connectome for pathways linking chemosensory neurons to neck motor neurons, and prune the resulting network based on both experimental considerations and several simplifying assumptions. We then use an evolutionary algorithm to find possible values for the unknown electrophsyiological parameters in the network such that the behavioral performance of the entire model is optimized to match that of the animal. Multiple runs of the evolutionary algorithm produce an ensemble of such models. We analyze in some detail the mechanisms by which one of the best evolved circuits operates and characterize the similarities and differences between this mechanism and other solutions in the ensemble. Finally, we propose a series of experiments to determine which of these alternatives the worm may be using.

Impaired structural motor connectome in amyotrophic lateral sclerosis.

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Esther Verstraete

Full Text Available Amyotrophic lateral sclerosis (ALS is a severe neurodegenerative disease selectively affecting upper and lower motor neurons. Patients with ALS suffer from progressive paralysis and eventually die on average after three years. The underlying neurobiology of upper motor neuron degeneration and its effects on the complex network of the brain are, however, largely unknown. Here, we examined the effects of ALS on the structural brain network topology in 35 patients with ALS and 19 healthy controls. Using diffusion tensor imaging (DTI, the brain network was reconstructed for each individual participant. The connectivity of this reconstructed brain network was compared between patients and controls using complexity theory without--a priori selected--regions of interest. Patients with ALS showed an impaired sub-network of regions with reduced white matter connectivity (p = 0.0108, permutation testing. This impaired sub-network was strongly centered around primary motor regions (bilateral precentral gyrus and right paracentral lobule, including secondary motor regions (bilateral caudal middle frontal gyrus and pallidum as well as high-order hub regions (right posterior cingulate and precuneus. In addition, we found a significant reduction in overall efficiency (p = 0.0095 and clustering (p = 0.0415. From our findings, we conclude that upper motor neuron degeneration in ALS affects both primary motor connections as well as secondary motor connections, together composing an impaired sub-network. The degenerative process in ALS was found to be widespread, but interlinked and targeted to the motor connectome.

Impaired structural motor connectome in amyotrophic lateral sclerosis.

Science.gov (United States)

Verstraete, Esther; Veldink, Jan H; Mandl, Rene C W; van den Berg, Leonard H; van den Heuvel, Martijn P

2011-01-01

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease selectively affecting upper and lower motor neurons. Patients with ALS suffer from progressive paralysis and eventually die on average after three years. The underlying neurobiology of upper motor neuron degeneration and its effects on the complex network of the brain are, however, largely unknown. Here, we examined the effects of ALS on the structural brain network topology in 35 patients with ALS and 19 healthy controls. Using diffusion tensor imaging (DTI), the brain network was reconstructed for each individual participant. The connectivity of this reconstructed brain network was compared between patients and controls using complexity theory without--a priori selected--regions of interest. Patients with ALS showed an impaired sub-network of regions with reduced white matter connectivity (p = 0.0108, permutation testing). This impaired sub-network was strongly centered around primary motor regions (bilateral precentral gyrus and right paracentral lobule), including secondary motor regions (bilateral caudal middle frontal gyrus and pallidum) as well as high-order hub regions (right posterior cingulate and precuneus). In addition, we found a significant reduction in overall efficiency (p = 0.0095) and clustering (p = 0.0415). From our findings, we conclude that upper motor neuron degeneration in ALS affects both primary motor connections as well as secondary motor connections, together composing an impaired sub-network. The degenerative process in ALS was found to be widespread, but interlinked and targeted to the motor connectome.

Human-scientific Planning Theory

OpenAIRE

Hagen, Aksel

1998-01-01

This working report is a paper written to XII AESOP Congress 22 – 25 July 1998, Aveiro, Portugal. It is a presentation of human-scientific action theory and its linkage to planning, both planning theory and planning practice. Human-scientific action theory is created by professor Gunnar Olsson and professor José Luis Ramírez, Nordic School of Planning, Stockholm. Planning is primarily a practical and reflective activity. The notion ”Planning” may, therefore, describe the activi...

An affected core drives network integration deficits of the structural connectome in 22q11.2 deletion syndrome

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František Váša

2016-01-01

Full Text Available Chromosome 22q11.2 deletion syndrome (22q11DS is a genetic disease known to lead to cerebral structural alterations, which we study using the framework of the macroscopic white-matter connectome. We create weighted connectomes of 44 patients with 22q11DS and 44 healthy controls using diffusion tensor magnetic resonance imaging, and perform a weighted graph theoretical analysis. After confirming global network integration deficits in 22q11DS (previously identified using binary connectomes, we identify the spatial distribution of regions responsible for global deficits. Next, we further characterize the dysconnectivity of the deficient regions in terms of sub-network properties, and investigate their relevance with respect to clinical profiles. We define the subset of regions with decreased nodal integration (evaluated using the closeness centrality measure as the affected core (A-core of the 22q11DS structural connectome. A-core regions are broadly bilaterally symmetric and consist of numerous network hubs — chiefly parietal and frontal cortical, as well as subcortical regions. Using a simulated lesion approach, we demonstrate that these core regions and their connections are particularly important to efficient network communication. Moreover, these regions are generally densely connected, but less so in 22q11DS. These specific disturbances are associated to a rerouting of shortest network paths that circumvent the A-core in 22q11DS, “de-centralizing” the network. Finally, the efficiency and mean connectivity strength of an orbito-frontal/cingulate circuit, included in the affected regions, correlate negatively with the extent of negative symptoms in 22q11DS patients, revealing the clinical relevance of present findings. The identified A-core overlaps numerous regions previously identified as affected in 22q11DS as well as in schizophrenia, which approximately 30–40% of 22q11DS patients develop.

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

NARCIS (Netherlands)

Di Martino, A. (Adriana); O'Connor, D. (David); Chen, B. (Bosi); Alaerts, K. (Kaat); Anderson, J.S. (Jeffrey S.); Assaf, M. (Michal); Balsters, J.H. (Joshua H.); Baxter, L. (Leslie); Beggiato, A. (Anita); Bernaerts, S. (Sylvie); L.M.E. Blanken (Laura); Bookheimer, S.Y. (Susan Y.); Braden, B.B. (B. Blair); Byrge, L. (Lisa); Castellanos, F.X. (F. Xavier); Dapretto, M. (Mirella); R. Delorme (Richard); Fair, D.A. (Damien A.); Fishman, I. (Inna); Fitzgerald, J. (Jacqueline); L. Gallagher (Louise); Keehn, R.J.J. (R. Joanne Jao); Kennedy, D.P. (Daniel P.); Lainhart, J.E. (Janet E.); Luna, B. (Beatriz); S.H. Mostofsky (Stewart H.); Müller, R.-A. (Ralph-Axel); Nebel, M.B. (Mary Beth); Nigg, J.T. (Joel T.); O'Hearn, K. (Kirsten); Solomon, M. (Marjorie); R. Toro (Roberto); Vaidya, C.J. (Chandan J.); Wenderoth, N. (Nicole); T.J.H. White (Tonya); Craddock, R.C. (R. Cameron); Lord, C. (Catherine); Leventhal, B. (Bennett); Milham, M.P. (Michael P.)

2017-01-01

textabstractThe second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data

A theory of human error

Science.gov (United States)

Mcruer, D. T.; Clement, W. F.; Allen, R. W.

1981-01-01

Human errors tend to be treated in terms of clinical and anecdotal descriptions, from which remedial measures are difficult to derive. Correction of the sources of human error requires an attempt to reconstruct underlying and contributing causes of error from the circumstantial causes cited in official investigative reports. A comprehensive analytical theory of the cause-effect relationships governing propagation of human error is indispensable to a reconstruction of the underlying and contributing causes. A validated analytical theory of the input-output behavior of human operators involving manual control, communication, supervisory, and monitoring tasks which are relevant to aviation, maritime, automotive, and process control operations is highlighted. This theory of behavior, both appropriate and inappropriate, provides an insightful basis for investigating, classifying, and quantifying the needed cause-effect relationships governing propagation of human error.

Dynamics of the connectome in Huntington's disease: A longitudinal diffusion MRI study

OpenAIRE

Odish, Omar F.F.; Caeyenberghs, Karen; Hosseini, Hadi; van den Bogaard, Simon J.A.; Roos, Raymund A.C.; Leemans, Alexander

2015-01-01

Abstract Objectives To longitudinally investigate the connectome in different stages of Huntington's disease (HD) by applying graph theoretical analysis to diffusion MRI data. Experimental design We constructed weighted structural networks and calculated their topological properties. Twenty-two premanifest (preHD), 10 early manifest HD and 24 healthy controls completed baseline and 2 year follow-up scans. We stratified the preHD group based on their predicted years to disease onset into a far...

From static to temporal network theory: Applications to functional brain connectivity

Directory of Open Access Journals (Sweden)

William Hedley Thompson

2017-06-01

Full Text Available Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, interest has been growing in examining the temporal dynamics of the brain’s network activity. Although different approaches to capturing fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. This theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences, and engineering article but it has not been adopted to a great extent within network neuroscience. The objective of this article is twofold: (i to present a detailed description of the central tenets of temporal network theory and describe its measures, and; (ii to apply these measures to a resting-state fMRI dataset to illustrate their utility. Furthermore, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this article are freely available as the Python package Teneto. Temporal network theory is a subfield of network theory that has had limited application to date within network neuroscience. The aims of this work are to introduce temporal network theory, define the metrics relevant to the context of network neuroscience, and illustrate their potential by analyzing a resting-state fMRI dataset. We found both between-subjects and between-task differences that illustrate the potential for these tools to be applied in a wider context. Our tools for analyzing temporal networks have been released in a Python package called Teneto.

An evolutionary theory of human motivation.

Science.gov (United States)

Bernard, Larry C; Mills, Michael; Swenson, Leland; Walsh, R Patricia

2005-05-01

The authors review psychology's historical, competing perspectives on human motivation and propose a new comprehensive theory. The new theory is based on evolutionary principles as proposed by C. Darwin (1859) and modified by W. D. Hamilton (1964, 1996), R. L. Trivers (1971, 1972), and R. Dawkins (1989). The theory unifies biological, behavioral, and cognitive approaches to motivation. The theory is neuropsychological and addresses conscious and nonconscious processes that underlie motivation, emotion, and self-control. The theory predicts a hierarchical structure of motives that are measurable as individual differences in human behavior. These motives are related to social problem domains (D. B. Bugental, 2000; D. T. Kenrick, N. P. Li, & J. Butner, 2003), and each is hypothesized to solve a particular problem of human inclusive fitness.

Globally Efficient Brain Organization and Treatment Response in Psychosis: A Connectomic Study of Gyrification

OpenAIRE

Palaniyappan, Lena; Marques, Tiago Reis; Taylor, Heather; Mondelli, Valeria; Reinders, A. A. T. Simone; Bonaccorso, Stefania; Giordano, Annalisa; DiForti, Marta; Simmons, Andrew; David, Anthony S.; Pariante, Carmine M.; Murray, Robin M.; Dazzan, Paola

2016-01-01

Background: Converging evidence suggests that patients with first-episode psychosis who show a poor treatment response may have a higher degree of neurodevelopmental abnormalities than good Responders. Characterizing the disturbances in the relationship among brain regions (covariance) can provide more information on neurodevelopmental integrity than searching for localized changes in the brain. Graph-based connectomic approach can measure structural covariance thus providing information on t...

Mimesis: Linking Postmodern Theory to Human Behavior

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Dybicz, Phillip

2010-01-01

This article elaborates mimesis as a theory of causality used to explain human behavior. Drawing parallels to social constructionism's critique of positivism and naturalism, mimesis is offered as a theory of causality explaining human behavior that contests the current dominance of Newton's theory of causality as cause and effect. The contestation…

Compresso: Efficient Compression of Segmentation Data for Connectomics

KAUST Repository

Matejek, Brian

2017-09-03

Recent advances in segmentation methods for connectomics and biomedical imaging produce very large datasets with labels that assign object classes to image pixels. The resulting label volumes are bigger than the raw image data and need compression for efficient storage and transfer. General-purpose compression methods are less effective because the label data consists of large low-frequency regions with structured boundaries unlike natural image data. We present Compresso, a new compression scheme for label data that outperforms existing approaches by using a sliding window to exploit redundancy across border regions in 2D and 3D. We compare our method to existing compression schemes and provide a detailed evaluation on eleven biomedical and image segmentation datasets. Our method provides a factor of 600–2200x compression for label volumes, with running times suitable for practice.

NeuroBlocks – Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects

KAUST Repository

Al-Awami, Ali

2015-08-12

In the field of connectomics, neuroscientists acquire electron microscopy volumes at nanometer resolution in order to reconstruct a detailed wiring diagram of the neurons in the brain. The resulting image volumes, which often are hundreds of terabytes in size, need to be segmented to identify cell boundaries, synapses, and important cell organelles. However, the segmentation process of a single volume is very complex, time-intensive, and usually performed using a diverse set of tools and many users. To tackle the associated challenges, this paper presents NeuroBlocks, which is a novel visualization system for tracking the state, progress, and evolution of very large volumetric segmentation data in neuroscience. NeuroBlocks is a multi-user web-based application that seamlessly integrates the diverse set of tools that neuroscientists currently use for manual and semi-automatic segmentation, proofreading, visualization, and analysis. NeuroBlocks is the first system that integrates this heterogeneous tool set, providing crucial support for the management, provenance, accountability, and auditing of large-scale segmentations. We describe the design of NeuroBlocks, starting with an analysis of the domain-specific tasks, their inherent challenges, and our subsequent task abstraction and visual representation. We demonstrate the utility of our design based on two case studies that focus on different user roles and their respective requirements for performing and tracking the progress of segmentation and proofreading in a large real-world connectomics project.

Can human error theory explain non-adherence?

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Barber, Nick; Safdar, A; Franklin, Bryoney D

2005-08-01

To apply human error theory to explain non-adherence and examine how well it fits. Patients who were taking chronic medication were telephoned and asked whether they had been adhering to their medicine, and if not the reasons were explored and analysed according to a human error theory. Of 105 patients, 87 were contacted by telephone and they took part in the study. Forty-two recalled being non-adherent, 17 of them in the last 7 days; 11 of the 42 were intentionally non-adherent. The errors could be described by human error theory, and it explained unintentional non-adherence well, however, the application of 'rules' was difficult when considering mistakes. The consideration of error producing conditions and latent failures also revealed useful contributing factors. Human error theory offers a new and valuable way of understanding non-adherence, and could inform interventions. However, the theory needs further development to explain intentional non-adherence.

The Functional Connectome of Speech Control.

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Stefan Fuertinger

2015-07-01

Full Text Available In the past few years, several studies have been directed to understanding the complexity of functional interactions between different brain regions during various human behaviors. Among these, neuroimaging research installed the notion that speech and language require an orchestration of brain regions for comprehension, planning, and integration of a heard sound with a spoken word. However, these studies have been largely limited to mapping the neural correlates of separate speech elements and examining distinct cortical or subcortical circuits involved in different aspects of speech control. As a result, the complexity of the brain network machinery controlling speech and language remained largely unknown. Using graph theoretical analysis of functional MRI (fMRI data in healthy subjects, we quantified the large-scale speech network topology by constructing functional brain networks of increasing hierarchy from the resting state to motor output of meaningless syllables to complex production of real-life speech as well as compared to non-speech-related sequential finger tapping and pure tone discrimination networks. We identified a segregated network of highly connected local neural communities (hubs in the primary sensorimotor and parietal regions, which formed a commonly shared core hub network across the examined conditions, with the left area 4p playing an important role in speech network organization. These sensorimotor core hubs exhibited features of flexible hubs based on their participation in several functional domains across different networks and ability to adaptively switch long-range functional connectivity depending on task content, resulting in a distinct community structure of each examined network. Specifically, compared to other tasks, speech production was characterized by the formation of six distinct neural communities with specialized recruitment of the prefrontal cortex, insula, putamen, and thalamus, which collectively

Using Pareto optimality to explore the topology and dynamics of the human connectome.

Science.gov (United States)

Avena-Koenigsberger, Andrea; Goñi, Joaquín; Betzel, Richard F; van den Heuvel, Martijn P; Griffa, Alessandra; Hagmann, Patric; Thiran, Jean-Philippe; Sporns, Olaf

2014-10-05

Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.

Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome

Energy Technology Data Exchange (ETDEWEB)

Panigrahy, Ashok [Children' s Hospital Los Angeles, Department of Radiology, Los Angeles, CA (United States); Children' s Hospital of Pittsburgh of UPMC, Department of Pediatric Radiology, Pittsburgh, PA (United States); Wisnowski, Jessica L. [Children' s Hospital Los Angeles, Department of Radiology, Los Angeles, CA (United States); University of Southern California, Brain and Creativity Institute, Los Angeles, CA (United States); Furtado, Andre [Children' s Hospital of Pittsburgh of UPMC, Department of Pediatric Radiology, Pittsburgh, PA (United States); Lepore, Natasha [Children' s Hospital Los Angeles, Department of Radiology, Los Angeles, CA (United States); Paquette, Lisa [Children' s Hospital Los Angeles, Center for Fetal and Neonatal Medicine, Los Angeles, CA (United States); Bluml, Stefan [Children' s Hospital Los Angeles, Department of Radiology, Los Angeles, CA (United States); University of Southern California, Department of Biomedical Engineering, Los Angeles, CA (United States)

2012-01-15

For typically developing infants, the last trimester of fetal development extending into the first post-natal months is a period of rapid brain development. Infants who are born premature face significant risk of brain injury (e.g., intraventricular or germinal matrix hemorrhage and periventricular leukomalacia) from complications in the perinatal period and also potential long-term neurodevelopmental disabilities because these early injuries can interrupt normal brain maturation. Neuroimaging has played an important role in the diagnosis and management of the preterm infant. Both cranial US and conventional MRI techniques are useful in diagnostic and prognostic evaluation of preterm brain development and injury. Cranial US is highly sensitive for intraventricular hemorrhage (IVH) and provides prognostic information regarding cerebral palsy. Data are limited regarding the utility of MRI as a routine screening instrument for brain injury for all preterm infants. However, MRI might provide diagnostic or prognostic information regarding PVL and other types of preterm brain injury in the setting of specific clinical indications and risk factors. Further development of advanced MR techniques like volumetric MR imaging, diffusion tensor imaging, metabolic imaging (MR spectroscopy) and functional connectivity are necessary to provide additional insight into the molecular, cellular and systems processes that underlie brain development and outcome in the preterm infant. The adult concept of the ''connectome'' is also relevant in understanding brain networks that underlie the preterm brain. Knowledge of the preterm connectome will provide a framework for understanding preterm brain function and dysfunction, and potentially even a roadmap for brain plasticity. By combining conventional imaging techniques with more advanced techniques, neuroimaging findings will likely be used not only as diagnostic and prognostic tools, but also as biomarkers for long

Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome

International Nuclear Information System (INIS)

Panigrahy, Ashok; Wisnowski, Jessica L.; Furtado, Andre; Lepore, Natasha; Paquette, Lisa; Bluml, Stefan

2012-01-01

For typically developing infants, the last trimester of fetal development extending into the first post-natal months is a period of rapid brain development. Infants who are born premature face significant risk of brain injury (e.g., intraventricular or germinal matrix hemorrhage and periventricular leukomalacia) from complications in the perinatal period and also potential long-term neurodevelopmental disabilities because these early injuries can interrupt normal brain maturation. Neuroimaging has played an important role in the diagnosis and management of the preterm infant. Both cranial US and conventional MRI techniques are useful in diagnostic and prognostic evaluation of preterm brain development and injury. Cranial US is highly sensitive for intraventricular hemorrhage (IVH) and provides prognostic information regarding cerebral palsy. Data are limited regarding the utility of MRI as a routine screening instrument for brain injury for all preterm infants. However, MRI might provide diagnostic or prognostic information regarding PVL and other types of preterm brain injury in the setting of specific clinical indications and risk factors. Further development of advanced MR techniques like volumetric MR imaging, diffusion tensor imaging, metabolic imaging (MR spectroscopy) and functional connectivity are necessary to provide additional insight into the molecular, cellular and systems processes that underlie brain development and outcome in the preterm infant. The adult concept of the ''connectome'' is also relevant in understanding brain networks that underlie the preterm brain. Knowledge of the preterm connectome will provide a framework for understanding preterm brain function and dysfunction, and potentially even a roadmap for brain plasticity. By combining conventional imaging techniques with more advanced techniques, neuroimaging findings will likely be used not only as diagnostic and prognostic tools, but also as biomarkers for long-term neurodevelopmental

Human Capital as a Challenge for Economics Theory

Directory of Open Access Journals (Sweden)

Barbara Wyrzykowska

2014-12-01

Full Text Available The issue of human capital is increasingly attracting the attention of both theorists and practitioners, because at present human resources play a decisive role in the creation of competitive economies and business entities. Human capital and knowledge are becoming key factors in the area of entity competitiveness. Consequently, human capital is currently being analysed in a multi-faceted way in the context of numerous economic theories. The aim of this study is to summarize, analyse, and synthesise the information published on the subject of the theory of human capital and to present new theories and scientific paradigms. The theories presented in this study show that employees constitute the basic capital of modern organizations. One of the contemporary paradigms of modern management is the concept of knowledge-based economy and the paradigm of information technology. This article is based on literature studies and theoretical reflections of the author.

Theories about evolutionary origins of human hepatitis B virus in primates and humans

Directory of Open Access Journals (Sweden)

Breno Frederico de Carvalho Dominguez Souza

2014-09-01

Conclusion: Some hypotheses about the evolutionary origins of human hepatitis B virus have been debated since the ‘90s. One theory suggested a New World origin because of the phylogenetic co-segregation between some New World human hepatitis B virus genotypes F and H and woolly monkey human hepatitis B virus in basal sister-relationship to the Old World non-human primates and human hepatitis B virus variants. Another theory suggests an Old World origin of human hepatitis B virus, and that it would have been spread following prehistoric human migrations over 100,000 years ago. A third theory suggests a co-speciation of human hepatitis B virus in non-human primate hosts because of the proximity between the phylogeny of Old and New World non-human primate and their human hepatitis B virus variants. The importance of further research, related to the subject in South American wild fauna, is paramount and highly relevant for understanding the origin of human hepatitis B virus.

Predicting human age using regional morphometry and inter-regional morphological similarity

Science.gov (United States)

Wang, Xun-Heng; Li, Lihua

2016-03-01

The goal of this study is predicting human age using neuro-metrics derived from structural MRI, as well as investigating the relationships between age and predictive neuro-metrics. To this end, a cohort of healthy subjects were recruited from 1000 Functional Connectomes Project. The ages of the participations were ranging from 7 to 83 (36.17+/-20.46). The structural MRI for each subject was preprocessed using FreeSurfer, resulting in regional cortical thickness, mean curvature, regional volume and regional surface area for 148 anatomical parcellations. The individual age was predicted from the combination of regional and inter-regional neuro-metrics. The prediction accuracy is r = 0.835, p Pearson correlation coefficient between predicted ages and actual ages. Moreover, the LASSO linear regression also found certain predictive features, most of which were inter-regional features. The turning-point of the developmental trajectories in human brain was around 40 years old based on regional cortical thickness. In conclusion, structural MRI could be potential biomarkers for the aging in human brain. The human age could be successfully predicted from the combination of regional morphometry and inter-regional morphological similarity. The inter-regional measures could be beneficial to investigating human brain connectome.

Unraveling The Connectome: Visualizing and Abstracting Large-Scale Connectomics Data

KAUST Repository

Al-Awami, Ali K.

2017-04-30

We explore visualization and abstraction approaches to represent neuronal data. Neuroscientists acquire electron microscopy volumes to reconstruct a complete wiring diagram of the neurons in the brain, called the connectome. This will be crucial to understanding brains and their development. However, the resulting data is complex and large, posing a big challenge to existing visualization techniques in terms of clarity and scalability. We describe solutions to tackle the problems of scalability and cluttered presentation. We first show how a query-guided interactive approach to visual exploration can reduce the clutter and help neuroscientists explore their data dynamically. We use a knowledge-based query algebra that facilitates the interactive creation of queries. This allows neuroscientists to pose domain-specific questions related to their research. Simple queries can be combined to form complex queries to answer more sophisticated questions. We then show how visual abstractions from 3D to 2D can significantly reduce the visual clutter and add clarity to the visualization so that scientists can focus more on the analysis. We abstract the topology of 3D neurons into a multi-scale, relative distance-preserving subway map visualization that allows scientists to interactively explore the morphological and connectivity features of neuronal cells. We then focus on the process of acquisition, where neuroscientists segment electron microscopy images to reconstruct neurons. The segmentation process of such data is tedious, time-intensive, and usually performed using a diverse set of tools. We present a novel web-based visualization system for tracking the state, progress, and evolution of segmentation data in neuroscience. Our multi-user system seamlessly integrates a diverse set of tools. Our system provides support for the management, provenance, accountability, and auditing of large-scale segmentations. Finally, we present a novel architecture to render very large

Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.

Science.gov (United States)

Lai, Chien-Han; Wu, Yu-Te; Hou, Yuh-Ming

2017-08-01

The functional network analysis of whole brain is an emerging field for research in depression. We initiated this study to investigate which subnetwork is significantly altered within the functional connectome in major depressive disorder (MDD). The study enrolled 52 first-episode medication-naïve patients with MDD and 40 controls for functional network analysis. All participants received the resting-state functional imaging using a 3-Tesla magnetic resonance scanner. After preprocessing, we calculated the connectivity matrix of functional connectivity in whole brain for each subject. The network-based statistics of connectome was used to perform group comparisons between patients and controls. The correlations between functional connectivity and clinical parameters were also performed. MDD patients had significant alterations in the network involving "theory of mind" regions, such as the left precentral gyrus, left angular gyrus, bilateral rolandic operculums and left inferior frontal gyrus. The center node of significant network was the left angular gyrus. No significant correlations of functional connectivity within the subnetwork and clinical parameters were noted. Functional connectivity of "theory of mind" subnetwork may be the core issue for pathophysiology in MDD. In addition, the center role of parietal region should be emphasized in future study. Copyright © 2017. Published by Elsevier B.V.

Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets

OpenAIRE

Li, Lianwei; Ma, Zhanshan (Sam)

2016-01-01

The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health?the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples...

Human Capital Theory: A Holistic Criticism

Science.gov (United States)

Tan, Emrullah

2014-01-01

Human capital theory has had a profound impact on a range of disciplines from economics to education and sociology. The theory has always been the subject of bitter criticisms from the very beginning, but it has comfortably survived and expanded its influence over other research disciplines. Not surprisingly, a considerable number of criticisms…

Rate-distortion theory and human perception.

Science.gov (United States)

Sims, Chris R

2016-07-01

The fundamental goal of perception is to aid in the achievement of behavioral objectives. This requires extracting and communicating useful information from noisy and uncertain sensory signals. At the same time, given the complexity of sensory information and the limitations of biological information processing, it is necessary that some information must be lost or discarded in the act of perception. Under these circumstances, what constitutes an 'optimal' perceptual system? This paper describes the mathematical framework of rate-distortion theory as the optimal solution to the problem of minimizing the costs of perceptual error subject to strong constraints on the ability to communicate or transmit information. Rate-distortion theory offers a general and principled theoretical framework for developing computational-level models of human perception (Marr, 1982). Models developed in this framework are capable of producing quantitatively precise explanations for human perceptual performance, while yielding new insights regarding the nature and goals of perception. This paper demonstrates the application of rate-distortion theory to two benchmark domains where capacity limits are especially salient in human perception: discrete categorization of stimuli (also known as absolute identification) and visual working memory. A software package written for the R statistical programming language is described that aids in the development of models based on rate-distortion theory. Copyright © 2016 The Author. Published by Elsevier B.V. All rights reserved.

Toward A Multilevel Theory of Career Development: Advancing Human Resource Development Theory Building

Science.gov (United States)

Upton, Matthew G.; Egan, Toby Marshall

2007-01-01

The established limitations of career development (CD) theory and human resource development (HRD) theory building are addressed by expanding the framing of these issues to multilevel contexts. Multilevel theory building is an approach most effectively aligned with HRD literature and CD and HRD practice realities. An innovative approach multilevel…

Toward discovery science of human brain function

DEFF Research Database (Denmark)

Biswal, Bharat B; Mennes, Maarten; Zuo, Xi-Nian

2010-01-01

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints...... individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships...... in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/....

The impact of epilepsy surgery on the structural connectome and its relation to outcome

Directory of Open Access Journals (Sweden)

Peter N. Taylor

Full Text Available Background: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. Methods: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. Results: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. Conclusion: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only. Keywords: Connectome, Network, Temporal lobe epilepsy, Surgery, Machine learning, Support vector machine (SVM

A Behavioral Theory of Human Capital Integration

DEFF Research Database (Denmark)

Christensen, Jesper

design in fostering the integration and use of human capital is bounded by individual cognitive limitations that may lead employees to deviate from expected behavior, both individually and in collaboration. The thesis consists of three research papers relying on comprehensive longitudinal project data...... with one another. The overarching contribution of the thesis is to demonstrate, through the combination of psychological and organizational theory, how the ability of firms to properly activate and apply the knowledge held by their employees is fundamentally contingent on the interplay of cognitive...... of a behavioral theory of human capital integration....

Toward a Unified Theory of Human Reasoning.

Science.gov (United States)

Sternberg, Robert J.

1986-01-01

The goal of this unified theory of human reasoning is to specify what constitutes reasoning and to characterize the psychological distinction between inductive and deductive reasoning. The theory views reasoning as the controlled and mediated application of three processes (encoding, comparison and selective combination) to inferential rules. (JAZ)

Driving and driven architectures of directed small-world human brain functional networks.

Directory of Open Access Journals (Sweden)

Chaogan Yan

Full Text Available Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86 to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule. Further split-half analyses indicated that our results were highly reproducible between two

Theory analysis of the Dental Hygiene Human Needs Conceptual Model.

Science.gov (United States)

MacDonald, L; Bowen, D M

2017-11-01

Theories provide a structural knowing about concept relationships, practice intricacies, and intuitions and thus shape the distinct body of the profession. Capturing ways of knowing and being is essential to any professions' practice, education and research. This process defines the phenomenon of the profession - its existence or experience. Theory evaluation is a systematic criterion-based assessment of a specific theory. This study presents a theory analysis of the Dental Hygiene Human Needs Conceptual Model (DH HNCM). Using the Walker and Avant Theory Analysis, a seven-step process, the DH HNCM, was analysed and evaluated for its meaningfulness and contribution to dental hygiene. The steps include the following: (i) investigate the origins; (ii) examine relationships of the theory's concepts; (iii) assess the logic of the theory's structure; (iv) consider the usefulness to practice; (v) judge the generalizability; (vi) evaluate the parsimony; and (vii) appraise the testability of the theory. Human needs theory in nursing and Maslow's Hierarchy of Need Theory prompted this theory's development. The DH HNCM depicts four concepts based on the paradigm concepts of the profession: client, health/oral health, environment and dental hygiene actions, and includes validated eleven human needs that evolved overtime to eight. It is logical, simplistic, allows scientific predictions and testing, and provides a unique lens for the dental hygiene practitioner. With this model, dental hygienists have entered practice, knowing they enable clients to meet their human needs. For the DH HNCM, theory analysis affirmed that the model is reasonable and insightful and adds to the dental hygiene professions' epistemology and ontology. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

Science.gov (United States)

Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

2017-05-01

Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

General, crystallized and fluid intelligence are not associated with functional global network efficiency: A replication study with the human connectome project 1200 data set.

Science.gov (United States)

Kruschwitz, J D; Waller, L; Daedelow, L S; Walter, H; Veer, I M

2018-05-01

One hallmark example of a link between global topological network properties of complex functional brain connectivity and cognitive performance is the finding that general intelligence may depend on the efficiency of the brain's intrinsic functional network architecture. However, although this association has been featured prominently over the course of the last decade, the empirical basis for this broad association of general intelligence and global functional network efficiency is quite limited. In the current study, we set out to replicate the previously reported association between general intelligence and global functional network efficiency using the large sample size and high quality data of the Human Connectome Project, and extended the original study by testing for separate association of crystallized and fluid intelligence with global efficiency, characteristic path length, and global clustering coefficient. We were unable to provide evidence for the proposed association between general intelligence and functional brain network efficiency, as was demonstrated by van den Heuvel et al. (2009), or for any other association with the global network measures employed. More specifically, across multiple network definition schemes, ranging from voxel-level networks to networks of only 100 nodes, no robust associations and only very weak non-significant effects with a maximal R 2 of 0.01 could be observed. Notably, the strongest (non-significant) effects were observed in voxel-level networks. We discuss the possibility that the low power of previous studies and publication bias may have led to false positive results fostering the widely accepted notion of general intelligence being associated to functional global network efficiency. Copyright © 2018 Elsevier Inc. All rights reserved.

Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets.

Science.gov (United States)

Li, Lianwei; Ma, Zhanshan Sam

2016-08-16

The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health-the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples, we discovered that only 49 communities (less than 1%) satisfied the neutral theory, and concluded that human microbial communities are not neutral in general. The 49 positive cases, although only a tiny minority, do demonstrate the existence of neutral processes. We realize that the traditional doctrine of microbial biogeography "Everything is everywhere, but the environment selects" first proposed by Baas-Becking resolves the apparent contradiction. The first part of Baas-Becking doctrine states that microbes are not dispersal-limited and therefore are neutral prone, and the second part reiterates that the freely dispersed microbes must endure selection by the environment. Therefore, in most cases, it is the host environment that ultimately shapes the community assembly and tip the human microbiome to niche regime.

Human Resource Management: The need for theory and diversity

OpenAIRE

Weber, Wolfgang; Kabst, Rüdiger

2004-01-01

Human Resource Management as an academic discipline needs to be theoretically grounded, i.e. it requires support through theories, theory-driven empirical research and critiques. In doing so, different theoretical perspectives are addressed suggesting a problem-orientated theory selection which leads inevitably to theoretical diversity.

A Lesson on Social Role Theory: An Example of Human Behavior in the Social Environment Theory

OpenAIRE

Agnes M. Dulin

2007-01-01

This paper discusses the social role theory, a theory of Human Behavior in the Social Environment (HBSE). Relevance of this topic is briefly discussed, as well as a definition of the theory and its historical background. Empirical research that employs this theory will be discussed.Recommendations will be made for future theory development and implications for social work education will conclude the discussion.

THE THEORY OF CIVILIZATIONS THROUGH THE LENS OF CONTEMPORARY HUMANITIES

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T. V. Danylova

2016-06-01

Full Text Available Purpose. This paper invites reflections on the further development of civilizational theory through the lens of contemporary humanities. It argues that philosophy is one of the key dimensions of the integral theory of civilizations. The purpose is to promote dialogue-rich interdisciplinary civilizational approach with philosophical understanding of human essence at its core. Methodology. The author has used comparative historical analysis, along with hermeneutical methodology and interdisciplinary approach. Theoretical basis and results. Faced with the challenges of our time, researchers are turning to the civilizational approach, according to which world history appears to us as a colourful spectrum of the options for the development of humanity. At the present stage of scientific development the integral theory of civilizations seems to be the most productive tool for the interpretation of the events taking place in our world. Origianlity. The problem of human being is a key factor in understanding the dynamics of civilizational process and designing a promising theory of civilizations. Philosophy should occupy an important place in the development of a new theory of civilizations: philosophy is the spiritual quintessence of every epoch, every cultural and civilizational community. In particular, a new theory has to take into account both classic and contemporary investigations in the field of philosophical anthropology and theory of values. The increasing threat posed by the clash of civilizations can become a swan song of humanity. For the preservation and further development of the world civilization, there is no other choice but to elaborate the strategies, mechanisms for consultation and dialogue, cooperation and partnership of civilizations and states. That is why the urgent task is to create the certain philosophical position that will contribute to mutual understanding. Conclusions. It is important to involve philosophers in the

High-resolution fiber tract reconstruction in the human brain by means of three-dimensional polarized light imaging (3D-PLI

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Markus eAxer

2011-12-01

Full Text Available Functional interactions between different brain regions require connecting fiber tracts, the structural basis of the human connectome. To assemble a comprehensive structural understanding of neural network elements from the microscopic to the macroscopic dimensions, a multimodal and multiscale approach has to be envisaged. However, the integration of results from complementary neuroimaging techniques poses a particular challenge. In this paper, we describe a steadily evolving neuroimaging technique referred to as three-dimensional polarized light imaging (3D-PLI. It is based on the birefringence of the myelin sheaths surrounding axons, and enables the high-resolution analysis of myelinated axons constituting the fiber tracts. 3D-PLI provides the mapping of spatial fiber architecture in the postmortem human brain at a sub-millimeter resolution, i.e. at the mesoscale. The fundamental data structure gained by 3D-PLI is a comprehensive 3D vector field description of fibers and fiber tract orientations – the basis for subsequent tractography. To demonstrate how 3D-PLI can contribute to unravel and assemble the human connectome, a multiscale approach with the same technology was pursued. Two complementary state-of-the-art polarimeters providing different sampling grids (pixel sizes of 100 μm and 1.6 μm were used. To exemplarily highlight the potential of this approach, fiber orientation maps and 3D fiber models were reconstructed in selected regions of the brain (e.g., Corpus callosum, Internal capsule, Pons. The results demonstrate that 3D-PLI is an ideal tool to serve as an interface between the microscopic and macroscopic levels of organization of the human connectome.

Disrupted functional connectome in antisocial personality disorder.

Science.gov (United States)

Jiang, Weixiong; Shi, Feng; Liao, Jian; Liu, Huasheng; Wang, Tao; Shen, Celina; Shen, Hui; Hu, Dewen; Wang, Wei; Shen, Dinggang

2017-08-01

Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD.

Challenging (Strategic) Human Resource management Theory

NARCIS (Netherlands)

J. Paauwe (Jaap); J.P.P.E.F. Boselie (Paul)

2002-01-01

textabstractTo fully understand the relationship between human resource management and performance in different contexts, we are in need of a synthesis between resource-based theory and new institutionalism. We argue that differences in institutional settings (between for example countries or

A Theory of Human Needs Should Be Human-Centered, Not Animal-Centered: Commentary on Kenrick et al. (2010).

Science.gov (United States)

Kesebir, Selin; Graham, Jesse; Oishi, Shigehiro

2010-05-01

Kenrick et al. (2010, this issue) make an important contribution by presenting a theory of human needs within an evolutionary framework. In our opinion, however, this framework bypasses the human uniqueness that Maslow intended to capture in his theory. We comment on the unique power of culture in shaping human motivation at the phylogenetic, ontogenetic, and proximate levels. We note that culture-gene coevolution may be a more promising lead to a theory of human motivation than a mammalcentric evolutionary perspective. © The Author(s) 2010.

Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI

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Yeu-Sheng Tyan

2017-01-01

Full Text Available The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD, Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females age- and education-matched subjects (age range: 13 to 14 years. The structural connectome was obtained by graph theoretical and network-based statistical (NBS analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI.

Science.gov (United States)

Tyan, Yeu-Sheng; Liao, Jan-Ray; Shen, Chao-Yu; Lin, Yu-Chieh; Weng, Jun-Cheng

2017-01-01

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

Theories about evolutionary origins of human hepatitis B virus in primates and humans.

Science.gov (United States)

Souza, Breno Frederico de Carvalho Dominguez; Drexler, Jan Felix; Lima, Renato Santos de; Rosário, Mila de Oliveira Hughes Veiga do; Netto, Eduardo Martins

2014-01-01

The human hepatitis B virus causes acute and chronic hepatitis and is considered one of the most serious human health issues by the World Health Organization, causing thousands of deaths per year. There are similar viruses belonging to the Hepadnaviridae family that infect non-human primates and other mammals as well as some birds. The majority of non-human primate virus isolates were phylogenetically close to the human hepatitis B virus, but like the human genotypes, the origins of these viruses remain controversial. However, there is a possibility that human hepatitis B virus originated in primates. Knowing whether these viruses might be common to humans and primates is crucial in order to reduce the risk to humans. To review the existing knowledge about the evolutionary origins of viruses of the Hepadnaviridae family in primates. This review was done by reading several articles that provide information about the Hepadnaviridae virus family in non-human primates and humans and the possible origins and evolution of these viruses. The evolutionary origin of viruses of the Hepadnaviridae family in primates has been dated back to several thousand years; however, recent analyses of genomic fossils of avihepadnaviruses integrated into the genomes of several avian species have suggested a much older origin of this genus. Some hypotheses about the evolutionary origins of human hepatitis B virus have been debated since the '90s. One theory suggested a New World origin because of the phylogenetic co-segregation between some New World human hepatitis B virus genotypes F and H and woolly monkey human hepatitis B virus in basal sister-relationship to the Old World non-human primates and human hepatitis B virus variants. Another theory suggests an Old World origin of human hepatitis B virus, and that it would have been spread following prehistoric human migrations over 100,000 years ago. A third theory suggests a co-speciation of human hepatitis B virus in non-human primate

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

Science.gov (United States)

Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

2012-01-01

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Structural connectomics of anxious arousal in early adolescence: Translating clinical and ethological findings

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Paul B. Sharp

2017-01-01

Full Text Available Etiological explanations of clinical anxiety can be advanced through understanding the neural mechanisms associated with anxiety in youth prior to the emergence of psychopathology. In this vein, the present study sought to investigate how trait anxiety is related to features of the structural connectome in early adolescence. 40 adolescents (21 female, mean age = 13.49 years underwent a diffusion-weighted imaging scan. We hypothesized that the strength of several a priori defined structural connections would vary with anxious arousal based on previous work in human clinical neuroscience and adult rodent optogenetics. First, connection strength of caudate to rostral middle frontal gyrus was predicted to be anticorrelated with anxious arousal, predicated on extant work in clinically-diagnosed adolescents. Second, connection strength of amygdala to rostral anterior cingulate and to medial orbital frontal cortex would be positively and negatively correlated with anxious arousal, respectively, predicated on rodent optogenetics showing the former pathway is anxiogenic and the latter is anxiolytic. We also predicted that levels of anxiety would not vary with measures of global network topology, based on reported null findings. Results support that anxiety in early adolescence is associated with (1 the clinical biomarker connecting caudate to frontal cortex, and (2 the anxiogenic pathway connecting amygdala to rostral anterior cingulate, both in left but not right hemisphere. Findings support that in early adolescence, anxious arousal may be related to mechanisms that increase anxiogenesis, and not in a deficit in regulatory mechanisms that support anxiolysis.

Disrupted functional connectome in antisocial personality disorder

Science.gov (United States)

Jiang, Weixiong; Shi, Feng; Liao, Jian; Liu, Huasheng; Wang, Tao; Shen, Celina; Shen, Hui; Hu, Dewen

2017-01-01

Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD. PMID:27541949

Theory Development and Convergence of Human Resource Fields: Implications for Human Performance Technology

Science.gov (United States)

Cho, Yonjoo; Yoon, Seung Won

2010-01-01

This study examines major theory developments in human resource (HR) fields and discusses implications for human performance technology (HPT). Differentiated HR fields are converging to improve organizational performance through knowledge-based innovations. Ruona and Gibson (2004) made a similar observation and analyzed the historical evolution…

General features of the retinal connectome determine the computation of motion anticipation

Science.gov (United States)

Johnston, Jamie; Lagnado, Leon

2015-01-01

Motion anticipation allows the visual system to compensate for the slow speed of phototransduction so that a moving object can be accurately located. This correction is already present in the signal that ganglion cells send from the retina but the biophysical mechanisms underlying this computation are not known. Here we demonstrate that motion anticipation is computed autonomously within the dendritic tree of each ganglion cell and relies on feedforward inhibition. The passive and non-linear interaction of excitatory and inhibitory synapses enables the somatic voltage to encode the actual position of a moving object instead of its delayed representation. General rather than specific features of the retinal connectome govern this computation: an excess of inhibitory inputs over excitatory, with both being randomly distributed, allows tracking of all directions of motion, while the average distance between inputs determines the object velocities that can be compensated for. DOI: http://dx.doi.org/10.7554/eLife.06250.001 PMID:25786068

Introduction to the Special Issue on the Theory of Human Values

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Eldad Davidov

2012-04-01

Full Text Available Research on human values in the social sciences took of after Schwartz introduced his theory of basic human values in 1992. This special issue includes articles dealing with methods of data analysis applied to measurements of some or all of the values postulated by the theory and of other variables.

Quantum theory and human perception of the macro-world.

Science.gov (United States)

Aerts, Diederik

2014-01-01

We investigate the question of 'why customary macroscopic entities appear to us humans as they do, i.e., as bounded entities occupying space and persisting through time', starting from our knowledge of quantum theory, how it affects the behavior of such customary macroscopic entities, and how it influences our perception of them. For this purpose, we approach the question from three perspectives. Firstly, we look at the situation from the standard quantum angle, more specifically the de Broglie wavelength analysis of the behavior of macroscopic entities, indicate how a problem with spin and identity arises, and illustrate how both play a fundamental role in well-established experimental quantum-macroscopical phenomena, such as Bose-Einstein condensates. Secondly, we analyze how the question is influenced by our result in axiomatic quantum theory, which proves that standard quantum theory is structurally incapable of describing separated entities. Thirdly, we put forward our new 'conceptual quantum interpretation', including a highly detailed reformulation of the question to confront the new insights and views that arise with the foregoing analysis. At the end of the final section, a nuanced answer is given that can be summarized as follows. The specific and very classical perception of human seeing-light as a geometric theory-and human touching-only ruled by Pauli's exclusion principle-plays a role in our perception of macroscopic entities as ontologically stable entities in space. To ascertain quantum behavior in such macroscopic entities, we will need measuring apparatuses capable of its detection. Future experimental research will have to show if sharp quantum effects-as they occur in smaller entities-appear to be ontological aspects of customary macroscopic entities. It remains a possibility that standard quantum theory is an incomplete theory, and hence incapable of coping ultimately with separated entities, meaning that a more general theory will be needed.

Quantum Theory and Human Perception of the Macro-World

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Diederik eAerts

2014-06-01

Full Text Available We investigate the question of 'why customary macroscopic entities appear to us humans as they do, i.e. as bounded entities occupying space and persisting through time', starting from our knowledge of quantum theory, how it affects the behavior of such customary macroscopic entities, and how it influences our perception of them. For this purpose, we approach the question from three perspectives. Firstly, we look at the situation from the standard quantum angle, more specifically the de Broglie wavelength analysis of the behavior of macroscopic entities, indicate how a problem with spin and identity arises, and illustrate how both play a fundamental role in well-established experimental quantum-macroscopical phenomena, such as Bose-Einstein condensates. Secondly, we analyze how the question is influenced by our result in axiomatic quantum theory, which proves that standard quantum theory is structurally incapable of describing separated entities. Thirdly, we put forward our new `conceptual quantum interpretation', including a highly detailed reformulation of the question to confront the new insights and views that arise with the foregoing analysis. At the end of the final section, a nuanced answer is given that can be summarized as follows. The specific and very classical perception of human seeing -- light as a geometric theory -- and human touching -- only ruled by Pauli's exclusion principle -- plays a role in our perception of macroscopic entities as ontologically stable objects in space. To ascertain quantum behavior in such macroscopic entities, we will need measuring apparatuses capable of its detection. Future experimental research will have to show if sharp quantum effects -- as they occur in smaller entities -- appear to be ontological aspects of customary macroscopic entities. It remains a possibility that standard quantum theory is an incomplete theory, and hence incapable of coping with separated entities, meaning that a more general

The human capital theory. Encouragement and criticism

Czech Academy of Sciences Publication Activity Database

Kolomiiets, Uliana; Petrushenko, Y.

2017-01-01

Roč. 1, č. 1 (2017), s. 77-80 ISSN 2520-6621 Institutional support: RVO:67985998 Keywords : human capital * Mincerian theory * labor economics Subject RIV: AH - Economics http://armgpublishing.sumdu.edu.ua/journals/sec/issue-1/article-9/

The human capital theory. Encouragement and criticism

Czech Academy of Sciences Publication Activity Database

Kolomiiets, Uliana; Petrushenko, Y.

2017-01-01

Roč. 1, č. 1 (2017), s. 77-80 ISSN 2520-6621 Institutional support: Progres-Q24 Keywords : human capital * Mincerian theory * labor economics Subject RIV: AH - Economics http://armgpublishing.sumdu.edu.ua/journals/sec/issue-1/article-9/

A Theory for the Origin of Human Menopause.

Science.gov (United States)

Takahashi, Mike; Singh, Rama S; Stone, John

2016-01-01

A complete and compelling evolutionary explanation for the origin of human menopause is wanting. Menopause onset is defined clinically as the final menses, confirmed after 1 year without menstruation. The theory proposed herein explains at multiple levels - ultimately genetic but involving (1) behavioral, (2) life history, and (3) social changes - the origin and evolution of menopause in women. Individuals in Lower Paleolithic human populations were characterized by short lifespans with diminished late-age survival and fertility, similar to contemporary chimpanzees, and thence were subject to three changes. (1) A mating behavior change was established in which only young women reproduced, thereby rendering as effectively neutral female-specific late-onset fertility-diminishing mutations, which accumulated subsequently. (2) A lifespan increase was manifested adaptively, revealing the reproductive senescence phenotype encoded in late-onset fertility-diminishing mutation genotypes, which, heretofore, had been unexpressed in the shorter lifespan. (3) A social interaction change emerged exaptively, when older non-reproductive women exclusively started assisting in rearing grandchildren rather than giving birth to and caring for their own children, ultimately leading to menstrual cycle cessation. The changes associate in a one-to-one manner with existing, non-mutually exclusive hypotheses for the origin of human menopause. Evidence for each hypothesis and its associated change having occurred are reviewed, and the hypotheses are combined in a synthetic theory for the origin of human menopause. The new theory simultaneously addresses the main theoretical problem with each hypothesis and yields predictions for future testing.

The missing link: Predicting connectomes from noisy and partially observed tract tracing data

DEFF Research Database (Denmark)

Hinne, Max; Meijers, Annet; Bakker, Rembrandt

2017-01-01

a high chance of being connected, while regions far apart are most likely disconnected in the connectome. After learning the latent embedding from the connections that we did observe, the latent space allows us to predict connections that have not been probed previously. We apply the methodology to two....... In this paper, we suggest that instead of probing all possible connections, hitherto unknown connections may be predicted from the data that is already available. Our approach uses a 'latent space model' that embeds the connectivity in an abstract physical space. Regions that are close in the latent space have...... connectivity data sets of the macaque, where we demonstrate that the latent space model is successful in predicting unobserved connectivity, outperforming two baselines and an alternative model in nearly all cases. Furthermore, we show how the latent spatial embedding may be used to integrate multimodal...

Decentring the Human? Towards a Post- Anthropocentric Standpoint Theory

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AnaLouise Keating

2013-01-01

Full Text Available Drawing on recent developments in virology and the work of Chicana queer-feminist Gloria Anzaldúa, this article explores the possibility of shifting from anthropocentric epistemologies (including feminist standpoint theories into more expansive, decentralized modes of knowledge production which are neither entirely human-centered nor fully post-human. We explore this shift through several parts: (1 A brief overview of recent critiques of anthropocentrism and the limitations in mainstream feminist standpoint theory’s ability to overcome this anthropocentrism; (2 an exploration of recent developments in virology’s promising alternatives to anthropocentrism’s narrow definition of the human; and (3 an analysis of Anzaldúa’s innovative nepantlera subjectivity and onto-epistemology as seen in her theory of conocimiento. Because scholars have yet to examine the post-anthropocentric (and posthumanist dimensions of Anzaldúa’s thought, but instead generally categorize her epistemology as an ethnic-specific feminist standpoint theory, her work offers a unique point of entry into these investigations.

Optimized connectome architecture for sensory-motor integration

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Jacob C. Worrell

2017-12-01

Full Text Available The intricate connectivity patterns of neural circuits support a wide repertoire of communication processes and functional interactions. Here we systematically investigate how neural signaling is constrained by anatomical connectivity in the mesoscale Drosophila (fruit fly brain network. We use a spreading model that describes how local perturbations, such as external stimuli, trigger global signaling cascades that spread through the network. Through a series of simple biological scenarios we demonstrate that anatomical embedding potentiates sensory-motor integration. We find that signal spreading is faster from nodes associated with sensory transduction (sensors to nodes associated with motor output (effectors. Signal propagation was accelerated if sensor nodes were activated simultaneously, suggesting a topologically mediated synergy among sensors. In addition, the organization of the network increases the likelihood of convergence of multiple cascades towards effector nodes, thereby facilitating integration prior to motor output. Moreover, effector nodes tend to coactivate more frequently than other pairs of nodes, suggesting an anatomically enhanced coordination of motor output. Altogether, our results show that the organization of the mesoscale Drosophila connectome imparts privileged, behaviorally relevant communication patterns among sensors and effectors, shaping their capacity to collectively integrate information. The complex network spanned by neurons and their axonal projections promotes a diverse set of functions. In the present report, we study how the topological organization of the fruit fly brain supports sensory-motor integration. Using a simple communication model, we demonstrate that the topology of this network allows efficient coordination among sensory and motor neurons. Our results suggest that brain network organization may profoundly shape the functional repertoire of this simple organism.

The Compression Flow as a Measure to Estimate the Cognitive Impairment Severity in Resting State fMRI and 18FDG-PET Alzheimer's Disease Connectomes

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Antonio Giuliano Zippo

2015-12-01

Full Text Available The human brain appears organized in compartments characterized by seemingly specific functional purposes on many spatial scales. A complementary functional state binds information from specialized districts to return what is called integrated information. This fundamental network dynamics undergoes to severe disarrays in diverse degenerative conditions such as Alzheimer's Diseases (AD. The AD represents a multifarious syndrome characterized by structural, functional and metabolic landmarks. In particular, in the early stages of AD, adaptive functional modifications of the brain networks mislead initial diagnoses because cognitive abilities may result indiscernible from normal subjects. As a matter of facts, current measures of functional integration fail to catch significant differences among normal, mild cognitive impairment (MCI and even AD subjects. The aim of this work is to introduce a new topological feature called Compression Flow (CF to finely estimate the extent of the functional integration in the brain networks. The method uses a Monte Carlo-like estimation of the information integration flows returning the compression ratio between the size of the injected information and the size of the condensed information within the network. We analyzed the resting state connectomes of 75 subjects of the Alzheimer's Disease Neuroimaging Initiative 2 (ADNI repository. Our analyses are focused on the 18FGD-PET and functional MRI (fMRI acquisitions in several clinical screening conditions. Results indicated that CF effectively discriminate MCI, AD and normal subjects by showing a significant decrease of the functional integration in the AD and MCI brain connectomes. This result did not emerge by using a set of common complex network statistics. Furthermore, CF was best correlated with individual clinical scoring scales. In conclusion, we presented a novel measure to quantify the functional integration that resulted efficient to discriminate

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

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Yu Sun

2017-11-01

Full Text Available Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging, we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging.

Interpretation of basic concepts in theories of human motor abilities

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Petrović Adam

2014-01-01

Full Text Available The basic aim of this research is to point to the possible language, logical and knowledge problems in interpretation and understanding of basic concepts in theories of motor abilities (TMA. Such manner of review is not directed only to 'mere understanding', it can lead to a new growth of scientific knowledge. Accordingly, the research question is set, i.e. the research issue: Is there a language, logical and knowledge agreement between basic concepts in the theories of human motor abilities? The answer to the set question direct that a more complete agreement between the basic concepts in the theories of human motor abilities should be searched in a scientific dialog between researchers of various beliefs.

Andragology and social capital theory: the implications for human resource development

NARCIS (Netherlands)

Kessels, Joseph; Poell, Rob F.

2004-01-01

The problem and the solution. This article portrays a perspective from andragogy, individual learning, and social capital theory as a contribution to the discussion on the relationship between adult learning theory and human resource development (HRD). Andragogy and social capital theory may offer a

Theorizing Translanguaging and Multilingual Literacies through Human Capital Theory

Science.gov (United States)

Smith, Patrick H.; Murillo, Luz A.

2015-01-01

In this conceptual article we invite multilingual researchers to consider the concept of translanguaging through the lens of human capital theory. Our thinking about the interconnections among human capital, multilingualism, and translanguaging is motivated by our research in border "colonias" and other minoritized communities in South…

Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

Science.gov (United States)

Munsell, B C; Wu, G; Fridriksson, J; Thayer, K; Mofrad, N; Desisto, N; Shen, D; Bonilha, L

2017-09-09

Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks that support naming ability. Importantly, naming is frequently impaired in other neurological disorders and by contrasting the neuronal structures supporting naming in TLE with other diseases, it will become possible to elucidate the common systems supporting naming. We aimed to evaluate the neuronal networks that support naming in TLE by using a machine learning algorithm intended to predict naming performance in subjects with medication refractory TLE using only the structural brain connectome reconstructed from diffusion tensor imaging. A connectome-based prediction framework was developed using network properties from anatomically defined brain regions across the entire brain, which were used in a multi-task machine learning algorithm followed by support vector regression. Nodal eigenvector centrality, a measure of regional network integration, predicted approximately 60% of the variance in naming. The nodes with the highest regression weight were bilaterally distributed among perilimbic sub-networks involving mainly the medial and lateral temporal lobe regions. In the context of emerging evidence regarding the role of large structural networks that support language processing, our results suggest intact naming relies on the integration of sub-networks, as opposed to being dependent on isolated brain areas. In the case of TLE, these sub-networks may be disproportionately indicative naming processes that are dependent semantic integration from memory and lexical retrieval, as opposed to multi-modal perception or motor speech production. Copyright © 2017. Published by Elsevier Inc.

The challenge of mapping the human connectome based on diffusion tractography

DEFF Research Database (Denmark)

Maier-Hein, Klaus H.; Neher, Peter F.; Houde, Jean-Christophe

2017-01-01

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tra...

The challenge of mapping the human connectome based on diffusion tractography

NARCIS (Netherlands)

Maier-Hein, Klaus H; Neher, Peter F; Houde, Jean-Christophe; Côté, Marc-Alexandre; Garyfallidis, Eleftherios; Zhong, Jidan; Chamberland, Maxime; Yeh, Fang-Cheng; Lin, Ying-Chia; Ji, Qing; Reddick, Wilburn E; Glass, John O; Chen, David Qixiang; Feng, Yuanjing; Gao, Chengfeng; Wu, Ye; Ma, Jieyan; Renjie, H; Li, Qiang; Westin, Carl Fredrik; Deslauriers-Gauthier, Samuel; González, J Omar Ocegueda; Paquette, Michael; St-Jean, Samuel; Girard, Gabriel; Rheault, François; Sidhu, Jasmeen; Tax, Chantal M.W.; Guo, Fenghua; Mesri, Hamed Y.; Dávid, Szabolcs; Froeling, Martijn; Heemskerk, Anneriet M.; Leemans, Alexander; Boré, Arnaud; Pinsard, Basile; Bedetti, Christophe; Desrosiers, Matthieu; Brambati, Simona; Doyon, Julien; Sarica, Alessia; Vasta, Roberta; Cerasa, Antonio; Quattrone, Aldo; Yeatman, Jason; Khan, Ali R.; Hodges, Wes; Alexander, Simon; Romascano, David; Barakovic, Muhamed; Auría, Anna; Esteban, Oscar; Lemkaddem, Alia; Thiran, Jean-Philippe; Cetingul, H Ertan; Odry, Benjamin L; Mailhe, Boris; Nadar, Mariappan S; Pizzagalli, Fabrizio; Prasad, Gautam; Villalon-Reina, Julio E; Galvis, Justin; Thompson, Paul M.; Requejo, Francisco De Santiago; Laguna, Pedro Luque; Lacerda, Luis Miguel; Barrett, Rachel; Dell'Acqua, Flavio; Catani, Marco; Petit, Laurent; Caruyer, Emmanuel; Daducci, Alessandro; Dyrby, Tim B; Holland-Letz, Tim; Hilgetag, Claus C.; Stieltjes, Bram; Descoteaux, Maxime

2017-01-01

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international

Modeling Mixed Groups of Humans and Robots with Reflexive Game Theory

Science.gov (United States)

Tarasenko, Sergey

The Reflexive Game Theory is based on decision-making principles similar to the ones used by humans. This theory considers groups of subjects and allows to predict which action from the set each subject in the group will choose. It is possible to influence subject's decision in a way that he will make a particular choice. The purpose of this study is to illustrate how robots can refrain humans from risky actions. To determine the risky actions, the Asimov's Three Laws of robotics are employed. By fusing the RGT's power to convince humans on the mental level with Asimov's Laws' safety, we illustrate how robots in the mixed groups of humans and robots can influence on human subjects in order to refrain humans from risky actions. We suggest that this fusion has a potential to device human-like motor behaving and looking robots with the human-like decision-making algorithms.

On the application of motivation theory to human factors/ergonomics: motivational design principles for human-technology interaction.

Science.gov (United States)

Szalma, James L

2014-12-01

Motivation is a driving force in human-technology interaction. This paper represents an effort to (a) describe a theoretical model of motivation in human technology interaction, (b) provide design principles and guidelines based on this theory, and (c) describe a sequence of steps for the. evaluation of motivational factors in human-technology interaction. Motivation theory has been relatively neglected in human factors/ergonomics (HF/E). In both research and practice, the (implicit) assumption has been that the operator is already motivated or that motivation is an organizational concern and beyond the purview of HF/E. However, technology can induce task-related boredom (e.g., automation) that can be stressful and also increase system vulnerability to performance failures. A theoretical model of motivation in human-technology interaction is proposed, based on extension of the self-determination theory of motivation to HF/E. This model provides the basis for both future research and for development of practical recommendations for design. General principles and guidelines for motivational design are described as well as a sequence of steps for the design process. Human motivation is an important concern for HF/E research and practice. Procedures in the design of both simple and complex technologies can, and should, include the evaluation of motivational characteristics of the task, interface, or system. In addition, researchers should investigate these factors in specific human-technology domains. The theory, principles, and guidelines described here can be incorporated into existing techniques for task analysis and for interface and system design.

Human factors and fuzzy set theory for safety analysis

International Nuclear Information System (INIS)

Nishiwaki, Y.

1987-01-01

Human reliability and performance is affected by many factors: medical, physiological and psychological, etc. The uncertainty involved in human factors may not necessarily be probabilistic, but fuzzy. Therefore, it is important to develop a theory by which both the non-probabilistic uncertainties, or fuzziness, of human factors and the probabilistic properties of machines can be treated consistently. In reality, randomness and fuzziness are sometimes mixed. From the mathematical point of view, probabilistic measures may be considered a special case of fuzzy measures. Therefore, fuzzy set theory seems to be an effective tool for analysing man-machine systems. The concept 'failure possibility' based on fuzzy sets is suggested as an approach to safety analysis and fault diagnosis of a large complex system. Fuzzy measures and fuzzy integrals are introduced and their possible applications are also discussed. (author)

[From humanism to nihilism: dialectics on Jean Watson's caring theory].

Science.gov (United States)

Krol, Pawel J; Lavoie, Mireille

2015-09-01

nursing today is heir to values that have developed over many years. In addition to the values of human care, present-day nursing embraces values that shape our modern world. This dialectical study first traces the evolution of a number of the traditional values associated with human care that nursing has retained. It goes on to show how some of the values of human care have been cast aside in favour of modern--neoliberal, technocratic and bureaucratic--values which have in turn given rise to disturbing problems of instrumentalization. Watson's theory of caring proposes two ways to remedy such instrumentalization: espousing a transcendental, metaphysical mode of thought and adopting an altruistic humanism. However, many critics have questioned the theoretical consistency and very legitimacy of the theory as a means of dealing with instrumentalization. this study analyses Watson's proposals, using a Nietzschean dialectic approach to test them and to suggest possible solutions. Significant problems in terms of both consistency and relevance are brought to light, tending to refute Watson's notions. the study findings suggest that the application of Watson's theory may paradoxically perpetuate dualism and nihilism and, rather than curb their invasive impact, lead inevitably to a conversion to instrumental values. it's suggested an alternative, ethics-of-life approach based on the synthesis of our dialectics that would foster a return to, and respect for, humanity's essential nature.

An Energy Model for Viewing Embodied Human Capital Theory

Science.gov (United States)

Kaufman, Neil A.; Geroy, Gary D.

2007-01-01

Human capital development is one of the emerging areas of study with regard to social science theory, practice, and research. A relatively new concept, human capital is described in terms of individual knowledge skills and experience. It is currently expressed as a function of education as well as a measure of economic activity. Little theory…

Disruption of structure–function coupling in the schizophrenia connectome

Directory of Open Access Journals (Sweden)

Luca Cocchi

2014-01-01

Full Text Available Neuroimaging studies have demonstrated that the phenomenology of schizophrenia maps onto diffuse alterations in large-scale functional and structural brain networks. However, the relationship between structural and functional deficits remains unclear. To answer this question, patients with established schizophrenia and matched healthy controls underwent resting-state functional and diffusion weighted imaging. The network-based statistic was used to characterize between-group differences in whole-brain functional connectivity. Indices of white matter integrity were then estimated to assess the structural correlates of the functional alterations observed in patients. Finally, group differences in the relationship between indices of functional and structural brain connectivity were determined. Compared to controls, patients with schizophrenia showed decreased functional connectivity and impaired white matter integrity in a distributed network encompassing frontal, temporal, thalamic, and striatal regions. In controls, strong interregional coupling in neural activity was associated with well-myelinated white matter pathways in this network. This correspondence between structure and function appeared to be absent in patients with schizophrenia. In two additional disrupted functional networks, encompassing parietal, occipital, and temporal cortices, the relationship between function and structure was not affected. Overall, results from this study highlight the importance of considering not only the separable impact of functional and structural connectivity deficits on the pathoaetiology of schizophrenia, but also the implications of the complex nature of their interaction. More specifically, our findings support the core nature of fronto-striatal, fronto-thalamic, and fronto-temporal abnormalities in the schizophrenia connectome.

A philosophical theory on human communication and modern physics: e(,2)c(,2)H('2)T energy-exchange and consciousness-change toward humanism, healing, and transformation

Science.gov (United States)

Jenkins-Tate, Marnishia Laverne

This dissertation addresses the need for a body of human communication theory that can be useful toward advancing personal and social transformation. Of the humanistic genre, it suggests that there is a need to promote humanism, healing, and personal transformation in the non-clinical settings of everyday living. Three questions guide the effort. First, it asks: what kind of human communication theory might describe some of the underlying dynamics of human interaction, while also suggesting ways to improve the quality of interactions of any related philosophical theory be grounded by some scientific discipline? Then finally, it asks: how might these proposed concepts be captured in a manner that can be useful to human beings in everyday human interaction? Extending the work of modern physics to the realm of human communication, the theory integrates conceptual aspects of quantum theory, relativity theory, communication accommodation theory, and various nonverbal communication theory. Then, it proposes the philosophical framework for a new body of theory which it calls the energy-exchange theory of human communication. Treating human beings as living forms of matter, it suggests that ``energy'' is the life-force that sustains all human beings, and that ``consciousness'' is that qualitative level of development at which energy manifests itself in the human experience. It proposes that human beings have the capacity to exchange energy and influence consciousness during the human communication process, and that these interactions can advance humanism, healing, and transformation-which it proposes are the higher states and levels of human consciousness. Thus, this research effort sought to know and to describe a phenomenon that is the interactive human being; and to suggest useful ways that this volitional being can know and transform itself through human interaction. With verisimilitude as a driving factor in describing human beings as communicators, the research is

Using a systems orientation and foundational theory to enhance theory-driven human service program evaluations.

Science.gov (United States)

Wasserman, Deborah L

2010-05-01

This paper offers a framework for using a systems orientation and "foundational theory" to enhance theory-driven evaluations and logic models. The framework guides the process of identifying and explaining operative relationships and perspectives within human service program systems. Self-Determination Theory exemplifies how a foundational theory can be used to support the framework in a wide range of program evaluations. Two examples illustrate how applications of the framework have improved the evaluators' abilities to observe and explain program effect. In both exemplars improvements involved addressing and organizing into a single logic model heretofore seemingly disparate evaluation issues regarding valuing (by whose values); the role of organizational and program context; and evaluation anxiety and utilization. Copyright 2009 Elsevier Ltd. All rights reserved.

The Superior Fronto-Occipital Fasciculus in the Human Brain Revealed by Diffusion Spectrum Imaging Tractography: An Anatomical Reality or a Methodological Artifact?

Science.gov (United States)

Bao, Yue; Wang, Yong; Wang, Wei; Wang, Yibao

2017-01-01

The existence of the superior fronto-occipital fasciculus (SFOF) in the human brain remains controversial. The aim of the present study was to clarify the existence, course, and terminations of the SFOF. High angular diffusion spectrum imaging (DSI) analysis was performed on six healthy adults and on a template of 842 subjects from the Human Connectome Project. To verify tractography results, we performed fiber microdissections of four post-mortem human brains. Based on DSI tractography, we reconstructed the SFOF in the subjects and the template from the Human Connectome Project that originated from the rostral and medial parts of the superior and middle frontal gyri. By tractography, we found that the fibers formed a compact fascicle at the level of the anterior horn of the lateral ventricle coursing above the head of caudate nucleus, medial to the corona radiate and under the corpus callosum (CC), and terminated at the parietal region via the lower part of the caudate nucleus. We consider that this fiber bundle observed by tractography is the SFOF, although it terminates mainly at the parietal region, rather than occipital lobe. By contrast, we were unable to identify a fiber bundle corresponding to the SFOF in our fiber dissection study. Although we did not provide definite evidence of the SFOF in the human brain, these findings may be useful for future studies in this field. PMID:29321729

The Superior Fronto-Occipital Fasciculus in the Human Brain Revealed by Diffusion Spectrum Imaging Tractography: An Anatomical Reality or a Methodological Artifact?

Directory of Open Access Journals (Sweden)

Yue Bao

2017-12-01

Full Text Available The existence of the superior fronto-occipital fasciculus (SFOF in the human brain remains controversial. The aim of the present study was to clarify the existence, course, and terminations of the SFOF. High angular diffusion spectrum imaging (DSI analysis was performed on six healthy adults and on a template of 842 subjects from the Human Connectome Project. To verify tractography results, we performed fiber microdissections of four post-mortem human brains. Based on DSI tractography, we reconstructed the SFOF in the subjects and the template from the Human Connectome Project that originated from the rostral and medial parts of the superior and middle frontal gyri. By tractography, we found that the fibers formed a compact fascicle at the level of the anterior horn of the lateral ventricle coursing above the head of caudate nucleus, medial to the corona radiate and under the corpus callosum (CC, and terminated at the parietal region via the lower part of the caudate nucleus. We consider that this fiber bundle observed by tractography is the SFOF, although it terminates mainly at the parietal region, rather than occipital lobe. By contrast, we were unable to identify a fiber bundle corresponding to the SFOF in our fiber dissection study. Although we did not provide definite evidence of the SFOF in the human brain, these findings may be useful for future studies in this field.

Liberating methodological thinking in human sciences from grand theories

DEFF Research Database (Denmark)

Kharlamov, Nikita; Baldursson, Einar Baldvin

2016-01-01

focus on the necessity of a “grand unified theory” at the expense of any and all alternative perspectives. Properties of grand theories are discussed on the examples of Giddens and Bourdieu. It is argued that grand theories hamper a more productive focus on concrete phenomena. Robert Merton’s focus......Many humanistic and social disciplines are naturally inclined to seek for human-, person-, self- centered focus, and develop a holistic theory of such. Such disciplines continually engage with philosophical, metaphysical and meta-theoretical perspectives. This engagement often leads to a singular...... on “middle range” theories is revisited and its continuing relevance is highlighted. The level of abstraction characteristic of such theories, as well as the way they engage with the empirical social reality, are discussed. The article concludes by considering the paradoxical reductionism that can...

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

Science.gov (United States)

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

Maslow's Theory of Human Motivation and its Deep Roots in Individualism: Interrogating Maslow's Applicability in Africa

OpenAIRE

Mawere, Munyaradzi; Mubaya, Tapuwa R.; van Reisen, Mirjam; Stam, van, Gertjan; Mawere, Munyaradzi; Nhemachena, Artwell

2016-01-01

Since the postulation of Abraham Maslow's theory of human motivation, the theory has been celebrated as the determining factor to account for and explain human wants and needs. While the theory has its genealogy from an individualistic society, the United States of America, where it was crafted and propelled to take a stand as a universal theory determining human wants and needs across the world, little has been done to critically examine its seemingly perceived universality and applicability...

Watson’s Human Caring Theory: Pertinent Transpersonal and Humanities Concepts for Educators

Directory of Open Access Journals (Sweden)

Carey S. Clark

2016-04-01

Full Text Available Jean Watson’s Theory of Human Caring and the caring moment are based in part in the concepts of transpersonal psychology. This paper will provide a historical background around transpersonal psychology and how it relates to Watson’s human caring moment. The purpose of explicating these humanities-based concepts is to support nurses and nurse educators in creating a deeper understanding of Watson’s caring-healing moment as a time-space continuum, where the nurse’s caring supports a mutually created environment for healing. The article provides useful background information, as well as outlining simple steps to revising nursing curricula so that they become supportive of nursing students’ growth as transpersonal-caring beings.

The brain functional connectome is robustly altered by lack of sleep.

Science.gov (United States)

Kaufmann, Tobias; Elvsåshagen, Torbjørn; Alnæs, Dag; Zak, Nathalia; Pedersen, Per Ø; Norbom, Linn B; Quraishi, Sophia H; Tagliazucchi, Enzo; Laufs, Helmut; Bjørnerud, Atle; Malt, Ulrik F; Andreassen, Ole A; Roussos, Evangelos; Duff, Eugene P; Smith, Stephen M; Groote, Inge R; Westlye, Lars T

2016-02-15

Sleep is a universal phenomenon necessary for maintaining homeostasis and function across a range of organs. Lack of sleep has severe health-related consequences affecting whole-body functioning, yet no other organ is as severely affected as the brain. The neurophysiological mechanisms underlying these deficits are poorly understood. Here, we characterize the dynamic changes in brain connectivity profiles inflicted by sleep deprivation and how they deviate from regular daily variability. To this end, we obtained functional magnetic resonance imaging data from 60 young, adult male participants, scanned in the morning and evening of the same day and again the following morning. 41 participants underwent total sleep deprivation before the third scan, whereas the remainder had another night of regular sleep. Sleep deprivation strongly altered the connectivity of several resting-state networks, including dorsal attention, default mode, and hippocampal networks. Multivariate classification based on connectivity profiles predicted deprivation state with high accuracy, corroborating the robustness of the findings on an individual level. Finally, correlation analysis suggested that morning-to-evening connectivity changes were reverted by sleep (control group)-a pattern which did not occur after deprivation. We conclude that both, a day of waking and a night of sleep deprivation dynamically alter the brain functional connectome. Copyright © 2015 Elsevier Inc. All rights reserved.

State Education as High-Yield Investment: Human Capital Theory in European Policy Discourse

Science.gov (United States)

Gillies, Donald

2011-01-01

Human Capital Theory has been an increasingly important phenomenon in economic thought over the last 50 years. The central role it affords to education has become even more marked in recent years as the concept of the "knowledge economy" has become a global concern. In this paper, the prevalence of Human Capital Theory within European…

Team management in the 21 st century: A human relations theory ...

African Journals Online (AJOL)

Team management in the 21 st century: A human relations theory angle. ... a team is about understanding human relation, that is, the manager understanding the ... The problem ranges from membership isolation to lack of communication and ...

Putting Gino's lesson to work: Actor-network theory, enacted humanity, and rehabilitation.

Science.gov (United States)

Abrams, Thomas; Gibson, Barbara E

2016-02-01

This article argues that rehabilitation enacts a particular understanding of "the human" throughout therapeutic assessment and treatment. Following Michel Callon and Vololona Rabeharisoa's "Gino's Lesson on Humanity," we suggest that this is not simply a top-down process, but is cultivated in the application and response to biomedical frameworks of human ability, competence, and responsibility. The emergence of the human is at once a materially contingent, moral, and interpersonal process. We begin the article by outlining the basics of the actor-network theory that underpins "Gino's Lesson on Humanity." Next, we elucidate its central thesis regarding how disabled personhood emerges through actor-network interactions. Section "Learning Gino's lesson" draws on two autobiographical examples, examining the emergence of humanity through rehabilitation, particularly assessment measures and the responses to them. We conclude by thinking about how rehabilitation and actor-network theory might take this lesson on humanity seriously. © The Author(s) 2016.

Explicating Practicum Program Theory: A Case Example in Human Ecology

Science.gov (United States)

Chandler, Kathryn M. M.; Williamson, Deanna L.

2013-01-01

This study explicated the theory underpinning the Human Ecology Practicum Program offered in the Department of Human Ecology at the University of Alberta. The program has operated for 40 years but never been formally evaluated. Using a document analysis, focus group and individual interviews, and a stakeholder working group, we explored…

Neoclassical and Institutional Economics as Foundations for Human Resource Development Theory

Science.gov (United States)

Wang, Greg G.; Holton, Elwood F., III

2005-01-01

In an effort to more comprehensively understand economics as a foundation of human resource development (HRD), this article reviews economic theories and models pertinent to HRD research and theory building. By examining neoclassical and neoinstitutional schools of contemporary economics, especially the screening model and the internal labor…

Exploring patterns of alteration in Alzheimer’s disease brain networks: a combined structural and functional connectomics analysis

Directory of Open Access Journals (Sweden)

Fulvia Palesi

2016-09-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder characterized by a severe derangement of cognitive functions, primarily memory, in elderly subjects. As far as the functional impairment is concerned, growing evidence supports the disconnection syndrome hypothesis. Recent investigations using fMRI have revealed a generalized alteration of resting state networks in patients affected by AD and mild cognitive impairment (MCI. However, it was unclear whether the changes in functional connectivity were accompanied by corresponding structural network changes. In this work, we have developed a novel structural/functional connectomic approach: resting state fMRI was used to identify the functional cortical network nodes and diffusion MRI to reconstruct the fiber tracts to give a weight to internodal subcortical connections. Then, local and global efficiency were determined for different networks, exploring specific alterations of integration and segregation patterns in AD and MCI patients compared to healthy controls (HC. In the default mode network (DMN, that was the most affected, axonal loss and reduced axonal integrity appeared to compromise both local and global efficiency along posterior-anterior connections. In the basal ganglia network (BGN, disruption of white matter integrity implied that main alterations occurred in local microstructure. In the anterior insular network (AIN, neuronal loss probably subtended a compromised communication with the insular cortex. Cognitive performance, evaluated by neuropsychological examinations, revealed a dependency on integration and segregation of brain networks. These findings are indicative of the fact that cognitive deficits in AD could be associated not only with cortical alterations (revealed by fMRI but also with subcortical alterations (revealed by diffusion MRI that extend beyond the areas primarily damaged by neurodegeneration, towards the support of an emerging concept of AD as a

Toward a Reconstruction of Organizational Theory: Androcentric Bias in A. H. Maslow's Theory of Human Motivation and Self-Actualization.

Science.gov (United States)

Tietze, Irene Nowell; Shakeshaft, Charol

An exploration in the context of feminist science of one theoretical basis of educational administration--Abraham Maslow's theory of human motivation and self-actualization--finds an androcentric bias in Maslow's methodology, philosophical underpinnings, and theory formulation. Maslow's hypothetico-deductive methodology was based on a…

Annual Research Review: Growth connectomics – the organization and reorganization of brain networks during normal and abnormal development

Science.gov (United States)

Vértes, Petra E; Bullmore, Edward T

2015-01-01

Background We first give a brief introduction to graph theoretical analysis and its application to the study of brain network topology or connectomics. Within this framework, we review the existing empirical data on developmental changes in brain network organization across a range of experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans). Synthesis We discuss preliminary evidence and current hypotheses for how the emergence of network properties correlates with concomitant cognitive and behavioural changes associated with development. We highlight some of the technical and conceptual challenges to be addressed by future developments in this rapidly moving field. Given the parallels previously discovered between neural systems across species and over a range of spatial scales, we also review some recent advances in developmental network studies at the cellular scale. We highlight the opportunities presented by such studies and how they may complement neuroimaging in advancing our understanding of brain development. Finally, we note that many brain and mind disorders are thought to be neurodevelopmental in origin and that charting the trajectory of brain network changes associated with healthy development also sets the stage for understanding abnormal network development. Conclusions We therefore briefly review the clinical relevance of network metrics as potential diagnostic markers and some recent efforts in computational modelling of brain networks which might contribute to a more mechanistic understanding of neurodevelopmental disorders in future. PMID:25441756

Maslow's Theory of Human Motivation and its Deep Roots in Individualism : Interrogating Maslow's Applicability in Africa

NARCIS (Netherlands)

Mawere, Munyaradzi; Mubaya, Tapuwa R.; van Reisen, Mirjam; Stam, van Gertjan; Mawere, Munyaradzi; Nhemachena, Artwell

Since the postulation of Abraham Maslow's theory of human motivation, the theory has been celebrated as the determining factor to account for and explain human wants and needs. While the theory has its genealogy from an individualistic society, the United States of America, where it was crafted and

Goal Setting Theory: What It Implies for Strategic Human Resource Development

OpenAIRE

AVCI, Ömer

2016-01-01

Among numerous motivational theories, goal setting theory particularly can serve strategic human resource development practices. The goal-setting theory suggests that organizational goals have to be communicated clearly and the goals need to be specific enough. Another feature of goal-setting is that they need not be too easy or perceived to be impossible to fulfill. SHRD personnel should keep in mind that some employees prefer to work individually toward fulfilling a goal, while others prefe...

Theory of mind: A foundational component of human general intelligence.

Science.gov (United States)

Estes, David; Bartsch, Karen

2017-01-01

To understand the evolution of general intelligence, Burkart et al. endorse a "cultural intelligence approach," which emphasizes the critical importance of social interaction. We argue that theory of mind provides an essential foundation and shared perspective for the efficient ontogenetic transmission of crucial knowledge and skills during human development and, together with language, can account for superior human general intelligence.

Decentring the Human? Towards a Post- Anthropocentric Standpoint Theory

OpenAIRE

AnaLouise Keating; Kimberly Merenda

2013-01-01

Drawing on recent developments in virology and the work of Chicana queer-feminist Gloria Anzaldúa, this article explores the possibility of shifting from anthropocentric epistemologies (including feminist standpoint theories) into more expansive, decentralized modes of knowledge production which are neither entirely human-centered nor fully post-human. We explore this shift through several parts: (1) A brief overview of recent critiques of anthropocentrism and the limitations in mainstream fe...

Toward a Theory for the Design of Human Technologies

DEFF Research Database (Denmark)

Simonsen, Jesper; Hertzum, Morten; Nielsen, Jørgen Lerche

2014-01-01

Design is increasingly becoming a part of the university curriculum and research agenda. A theory about the pro-cess and practice of design might be important to estab-lish design as a main subject at universities. We believe it is in the interest of many design communities – not least...... the Participatory Design (PD) community – to engage in theorizing design, on the basis of our understanding of design and design practices. This theory could be posi-tioned as an alternative to other attempts to theorize design, for example the influential efforts of the Information Systems (IS) community. We urge...... the PD community to engage in collective theory building, and we present a framework intended to support our shared reflections on the design of human technologies....

Cortical Thought Theory: A Working Model of the Human Gestalt Mechanism.

Science.gov (United States)

1985-07-01

2. The Artificial Inteligence Perspective • -° 2.1 Introduction: Chapter Overview This chapter addresses the development of a...6 . . 2. The Artificial Intelligence Perspective ... .......... 9 2.1 Introduction: Chapter Overview .... ........... 9 2.2 The Problem 9...new unified theory of human brain function called Cortical Thought Theory (CTT). The analysis integrates the disciplines of Artificial Intelligence

Strategic Human Resource Metrics: A Perspective of the General Systems Theory

Directory of Open Access Journals (Sweden)

Chux Gervase Iwu

2016-04-01

Full Text Available Measuring and quantifying strategic human resource outcomes in relation to key performance criteria is essential to developing value-adding metrics. Objectives This paper posits (using a general systems lens that strategic human resource metrics should interpret the relationship between attitudinal human resource outcomes and performance criteria such as profitability, quality or customer service. Approach Using the general systems model as underpinning theory, the study assesses the variation in response to a Likert type questionnaire with twenty-four (24 items measuring the major attitudinal dispositions of HRM outcomes (employee commitment, satisfaction, engagement and embeddedness. Results A Chi-square test (Chi-square test statistic = 54.898, p=0.173 showed that variation in responses to the attitudinal statements occurred due to chance. This was interpreted to mean that attitudinal human resource outcomes influence performance as a unit of system components. The neutral response was found to be associated with the ‘reject’ response than the ‘acceptance’ response. Value The study offers suggestion on the determination of strategic HR metrics and recommends the use of systems theory in HRM related studies. Implications This study provides another dimension to human resource metrics by arguing that strategic human resource metrics should measure the relationship between attitudinal human resource outcomes and performance using a systems perspective.

Quality of Life Theory II. Quality of Life as the Realization of Life Potential: A Biological Theory of Human Being

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Soren Ventegodt

2003-01-01

Full Text Available This review presents one of the eight theories of the quality of life (QOL used for making the SEQOL (self-evaluation of quality of life questionnaire or the quality of life as realizing life potential. This theory is strongly inspired by Maslow and the review furthermore serves as an example on how to fulfill the demand for an overall theory of life (or philosophy of life, which we believe is necessary for global and generic quality-of-life research.Whereas traditional medical science has often been inspired by mechanical models in its attempts to understand human beings, this theory takes an explicitly biological starting point. The purpose is to take a close view of life as a unique entity, which mechanical models are unable to do. This means that things considered to be beyond the individual's purely biological nature, notably the quality of life, meaning in life, and aspirations in life, are included under this wider, biological treatise. Our interpretation of the nature of all living matter is intended as an alternative to medical mechanism, which dates back to the beginning of the 20th century. New ideas such as the notions of the human being as nestled in an evolutionary and ecological context, the spontaneous tendency of self-organizing systems for realization and concord, and the central role of consciousness in interpreting, planning, and expressing human reality are unavoidable today in attempts to scientifically understand all living matter, including human life.

The challenge of mapping the human connectome based on diffusion tractography.

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Maier-Hein, Klaus H; Neher, Peter F; Houde, Jean-Christophe; Côté, Marc-Alexandre; Garyfallidis, Eleftherios; Zhong, Jidan; Chamberland, Maxime; Yeh, Fang-Cheng; Lin, Ying-Chia; Ji, Qing; Reddick, Wilburn E; Glass, John O; Chen, David Qixiang; Feng, Yuanjing; Gao, Chengfeng; Wu, Ye; Ma, Jieyan; Renjie, H; Li, Qiang; Westin, Carl-Fredrik; Deslauriers-Gauthier, Samuel; González, J Omar Ocegueda; Paquette, Michael; St-Jean, Samuel; Girard, Gabriel; Rheault, François; Sidhu, Jasmeen; Tax, Chantal M W; Guo, Fenghua; Mesri, Hamed Y; Dávid, Szabolcs; Froeling, Martijn; Heemskerk, Anneriet M; Leemans, Alexander; Boré, Arnaud; Pinsard, Basile; Bedetti, Christophe; Desrosiers, Matthieu; Brambati, Simona; Doyon, Julien; Sarica, Alessia; Vasta, Roberta; Cerasa, Antonio; Quattrone, Aldo; Yeatman, Jason; Khan, Ali R; Hodges, Wes; Alexander, Simon; Romascano, David; Barakovic, Muhamed; Auría, Anna; Esteban, Oscar; Lemkaddem, Alia; Thiran, Jean-Philippe; Cetingul, H Ertan; Odry, Benjamin L; Mailhe, Boris; Nadar, Mariappan S; Pizzagalli, Fabrizio; Prasad, Gautam; Villalon-Reina, Julio E; Galvis, Justin; Thompson, Paul M; Requejo, Francisco De Santiago; Laguna, Pedro Luque; Lacerda, Luis Miguel; Barrett, Rachel; Dell'Acqua, Flavio; Catani, Marco; Petit, Laurent; Caruyer, Emmanuel; Daducci, Alessandro; Dyrby, Tim B; Holland-Letz, Tim; Hilgetag, Claus C; Stieltjes, Bram; Descoteaux, Maxime

2017-11-07

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Does Human Capital Theory Explain the Value of Higher Education? A South African Case Study

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van der Merwe, Alex

2010-01-01

A perennial debate in the economics of education is whether human capital or screening/signalling theories best explain the value of schooling and hence the private demand for, in particular, higher education. Human capital theory proposes that formal training such as that offered by higher education institutions improves the productive capacity…

Anthropologia transscendentalis. Kant's theory of human nature.

Science.gov (United States)

Battaglia, F

2012-01-01

In recent years mankind has greatly extended its knowledge of living things, in general, and itself, in particular. Such a wide-ranging body of knowledge has consequently led to the need for a theory to encompass it, that is, a coherent framework in which to systematically arrange mankind's understanding of itself, not only with regard to its physical nature, but to its individuality and sociality as well. Such a theory would moreover provide the means to mediate between the various domains of scientific and technological enquiry, on the one hand, and the cultural dimensions of human society, on the other. Already in the 18th century, Immanuel Kant strove to establish a discipline that was systematic, yet at the same time accessible. It was due to his efforts that philosophical anthropology was introduced into university curricula, to the benefit not only of philosophers, but of physicians and jurists as well. Kant's position is by no means prejudicial towards science. To the contrary, he was quite careful to appraise the impact of the sciences on the overall cognitive horizons of mankind and therefore on their potential to influence humankind's idea of itself. Clearly such a perspective is relevant to today's strongly felt need to reconcile modern neuroscience's revolutionary findings on the biological bases of the mind - of man's experience and behaviour - with the idea man needs of himself in order to orient his actions not only as individual but also as "citizen of the world" as well - something on which Kant worked with unremitting commitment throughout his entire research career. This article traces Kant's anthropological conception with regard to four specific issues: (1) its relation to science; (2) the relationship between empirical and transcendental in the speculative use and in practical use of reason; (3) the dialectic between what nature does and what human beings does, in the construction of humanity itself; (4) and finally about the character of the

Neuroanatomical correlates of childhood apraxia of speech: A connectomic approach.

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Fiori, Simona; Guzzetta, Andrea; Mitra, Jhimli; Pannek, Kerstin; Pasquariello, Rosa; Cipriani, Paola; Tosetti, Michela; Cioni, Giovanni; Rose, Stephen E; Chilosi, Anna

2016-01-01

Childhood apraxia of speech (CAS) is a paediatric speech sound disorder in which precision and consistency of speech movements are impaired. Most children with idiopathic CAS have normal structural brain MRI. We hypothesize that children with CAS have altered structural connectivity in speech/language networks compared to controls and that these altered connections are related to functional speech/language measures. Whole brain probabilistic tractography, using constrained spherical deconvolution, was performed for connectome generation in 17 children with CAS and 10 age-matched controls. Fractional anisotropy (FA) was used as a measure of connectivity and the connections with altered FA between CAS and controls were identified. Further, the relationship between altered FA and speech/language scores was determined. Three intra-hemispheric/interhemispheric subnetworks showed reduction of FA in CAS compared to controls, including left inferior (opercular part) and superior (dorsolateral, medial and orbital part) frontal gyrus, left superior and middle temporal gyrus and left post-central gyrus (subnetwork 1); right supplementary motor area, left middle and inferior (orbital part) frontal gyrus, left precuneus and cuneus, right superior occipital gyrus and right cerebellum (subnetwork 2); right angular gyrus, right superior temporal gyrus and right inferior occipital gyrus (subnetwork 3). Reduced FA of some connections correlated with diadochokinesis, oromotor skills, expressive grammar and poor lexical production in CAS. These findings provide evidence of structural connectivity anomalies in children with CAS across specific brain regions involved in speech/language function. We propose altered connectivity as a possible epiphenomenon of complex pathogenic mechanisms in CAS which need further investigation.

The Development of Altruism with Special Reference to Human Relationships: A 10-Stage Theory

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Hing Keung Ma

2017-10-01

Full Text Available All human relationships involve some form of cost and benefit and altruism forms the foundation upon which human relationships are built. In this paper, a taxonomy of human relationships in terms of altruism was constructed. In the proposed taxonomy, human relationships are categorized into three major groups: primary group, secondary group, and tertiary group. The primary group consists of members that are very closely related to each other either by genetic relatedness (e.g., parents, siblings, and cousins or social relatedness (e.g., mate and close friends or both. The secondary group consists of members that are socially related but also less closely related with each other (e.g., people of the same political or religious group, teachers, mentors, acquaintances, neighbors, working colleagues, and strangers. Lastly, the tertiary group consists of members of other species. A 10-stage theory of altruism with special reference to human relationships is proposed. The affective, cognitive, and relationship aspects of each stage are delineated in details. There are two developmental principles of altruism. The first principle states that the development of altruism follows the 10-stage theory and moves from Stage 1: Egoism toward the higher stages of altruism slowly. The second developmental principle states that the taxonomy of human relationships is valid at any stage of altruism development. In other words, people at any stage of altruism are more altruistic toward their kin and mate, and then close friends, extended family members, and so on. They are least altruistic toward enemies and members of non-human species. In summary, the proposed developmental principle of altruism and human relationships is logical and robust. It is formulated based on the major developmental and social psychological theories. The theory has the potential in providing a useful framework for future studies on the development and evolution of human relationships.

The Development of Altruism with Special Reference to Human Relationships: A 10-Stage Theory

Science.gov (United States)

Ma, Hing Keung

2017-01-01

All human relationships involve some form of cost and benefit and altruism forms the foundation upon which human relationships are built. In this paper, a taxonomy of human relationships in terms of altruism was constructed. In the proposed taxonomy, human relationships are categorized into three major groups: primary group, secondary group, and tertiary group. The primary group consists of members that are very closely related to each other either by genetic relatedness (e.g., parents, siblings, and cousins) or social relatedness (e.g., mate and close friends) or both. The secondary group consists of members that are socially related but also less closely related with each other (e.g., people of the same political or religious group, teachers, mentors, acquaintances, neighbors, working colleagues, and strangers). Lastly, the tertiary group consists of members of other species. A 10-stage theory of altruism with special reference to human relationships is proposed. The affective, cognitive, and relationship aspects of each stage are delineated in details. There are two developmental principles of altruism. The first principle states that the development of altruism follows the 10-stage theory and moves from Stage 1: Egoism toward the higher stages of altruism slowly. The second developmental principle states that the taxonomy of human relationships is valid at any stage of altruism development. In other words, people at any stage of altruism are more altruistic toward their kin and mate, and then close friends, extended family members, and so on. They are least altruistic toward enemies and members of non-human species. In summary, the proposed developmental principle of altruism and human relationships is logical and robust. It is formulated based on the major developmental and social psychological theories. The theory has the potential in providing a useful framework for future studies on the development and evolution of human relationships. PMID:29085818

The Development of Altruism with Special Reference to Human Relationships: A 10-Stage Theory.

Science.gov (United States)

Ma, Hing Keung

2017-01-01

All human relationships involve some form of cost and benefit and altruism forms the foundation upon which human relationships are built. In this paper, a taxonomy of human relationships in terms of altruism was constructed. In the proposed taxonomy, human relationships are categorized into three major groups: primary group, secondary group, and tertiary group. The primary group consists of members that are very closely related to each other either by genetic relatedness (e.g., parents, siblings, and cousins) or social relatedness (e.g., mate and close friends) or both. The secondary group consists of members that are socially related but also less closely related with each other (e.g., people of the same political or religious group, teachers, mentors, acquaintances, neighbors, working colleagues, and strangers). Lastly, the tertiary group consists of members of other species. A 10-stage theory of altruism with special reference to human relationships is proposed. The affective, cognitive, and relationship aspects of each stage are delineated in details. There are two developmental principles of altruism. The first principle states that the development of altruism follows the 10-stage theory and moves from Stage 1: Egoism toward the higher stages of altruism slowly. The second developmental principle states that the taxonomy of human relationships is valid at any stage of altruism development. In other words, people at any stage of altruism are more altruistic toward their kin and mate, and then close friends, extended family members, and so on. They are least altruistic toward enemies and members of non-human species. In summary, the proposed developmental principle of altruism and human relationships is logical and robust. It is formulated based on the major developmental and social psychological theories. The theory has the potential in providing a useful framework for future studies on the development and evolution of human relationships.

The historical character of human nature in Freud's theories.

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Zilbersheid, Uri

2013-06-01

In Freud' theories of human development, human nature is described and analyzed as essentially historical. At the core of human history is the restructuring of the sexual instinct and the death instinct (or its unique form as destructive impulses). The conscious, asked-for shaping of these two instincts, under the rule of the "reality principle", forms the basis of human society at all stages. This conscious restructuring has also unintended, unasked-for results, which are part of the historically developing human nature. The historical choice has been the building of human society as a social complex based on the de-eroticization of both the individual and society. Freud suggested that the historical process of changing human nature and maintaining the achieved new structure has mainly been an enterprise of enlightened political elite, which has imposed (in all societies) the various elements of the new nature upon the ordinary people. Human history is essentially a deed of the political sphere. In viewing human nature as consisting of both asked-for and unasked-for results of human conscious purposeful activity Freud belongs to the same historical school as Marx.

Natural Good Theories and the Value of Human Dignity.

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Muders, Sebastian

2016-04-01

One of the widely recognized facts about human dignity is its vastly divergent applicability-from highly controversial issues in bioethics to broader topics in political philosophy. A group of theories that this article subsumes under the header "natural good theories" appears to be especially fitted for normatively multifaceted notions like dignity. However, the heavy normative weight the concept of dignity has to bear due to the central position it occupies within these theories creates its own difficulties. As is shown in a discussion of Martha Nussbaum's capability conception of dignity, dignity appears to be unable to mirror the special normative relevance people want to assign to it in cases of great moral misconduct. The article provides a suggestion on how to solve this problem by means of paradigmatic cases that work as material constraints regarding the exact boundaries of dignity violations.

Seeking Humanizing Care in Patient-Centered Care Process: A Grounded Theory Study.

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Cheraghi, Mohammad Ali; Esmaeili, Maryam; Salsali, Mahvash

Patient-centered care is both a goal in itself and a tool for enhancing health outcomes. The application of patient-centered care in health care services globally however is diverse. This article reports on a study that sought to introduce patient-centered care. The aim of this study is to explore the process of providing patient-centered care in critical care units. The study used a grounded theory method. Data were collected on 5 critical care units in Tehran University of Medical Sciences. Purposive and theoretical sampling directed the collection of data using 29 semistructured interviews with 27 participants (nurses, patients, and physician). Data obtained were analyzed according to the analysis stages of grounded theory and constant comparison to identify the concepts, context, and process of the study. The core category of this grounded theory is "humanizing care," which consisted of 4 interrelated phases, including patient acceptance, purposeful patient assessment and identification, understanding patients, and patient empowerment. A core category of humanizing care integrated the theory. Humanizing care was an outcome and process. Patient-centered care is a dynamic and multifaceted process provided according to the nurses' understanding of the concept. Patient-centered care does not involve repeating routine tasks; rather, it requires an all-embracing understanding of the patients and showing respect for their values, needs, and preferences.

Parallel experience: how art and art theory can inform ethics in human research.

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Schwartz, L

2003-12-01

Trends in ethical research involving humans emphasise the importance of collaboration, of involving research subjects, alongside the researchers in the construction and implementation of research. This paper will explore parallels derived from another tradition of investigation of the human: art and art theory. An artist's inquiry into the problems of human research will be described, followed by the application of arguments from art theory to research practice. Recently artist Christine Borland has provided examples in which the lack of collaboration in research has caused injustice. Borland's work reflects these ethical dilemmas and questions the procedures and assumptions involved. In most cases the value of subject anonymity is called into question because it reduces the subjects' control over themselves. The application of art theory, which has already considered these problems, helps question and explore the ways in which the subject turned object of artistic or scientific interpretation can maintain some control and dignity.

Explanation of asymmetric dynamics of human water consumption in arid regions: prospect theory versus expected utility theory

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Tian, F.; Lu, Y.

2017-12-01

Based on socioeconomic and hydrological data in three arid inland basins and error analysis, the dynamics of human water consumption (HWC) are analyzed to be asymmetric, i.e., HWC increase rapidly in wet periods while maintain or decrease slightly in dry periods. Besides the qualitative analysis that in wet periods great water availability inspires HWC to grow fast but the now expanded economy is managed to sustain by over-exploitation in dry periods, two quantitative models are established and tested, based on expected utility theory (EUT) and prospect theory (PT) respectively. EUT states that humans make decisions based on the total expected utility, namely the sum of utility function multiplied by probability of each result, while PT states that the utility function is defined over gains and losses separately, and probability should be replaced by probability weighting function.

The Context and Values Inherent in Human Capital as Core Principles for New Economic Theory

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Winston P. Nagan

2018-05-01

Full Text Available This paper has a specific focus on the core foundation of New Economic Theory. That is, the focus on human capital and its implications for the theory and method of the new form of political economy. The central issue that is underlined is the importance of scientific and technological innovation and its necessary interdependence on global values and value analysis. The paper discusses the issue of scientific consciousness as a generator of technological value, and places scientific process at the heart of human consciousness. It discusses the complex interdependence of human relational subjectivity, scientific consciousness, and modern science. The paper draws attention to the problems of observation and participation, and the influence of modern quantum physics in drawing attention to aspects of human consciousness that go beyond the points of conventional science, and open up concern for the principle of non-locality. It explores human subjectivity in terms of the way in which “emotionalized behaviors” have effects on scientific objectivity. It also briefly touches on consciousness and its observable scientific role in the possible reconstruction of some aspects of reality. Mention is made of the Copenhagen perspective, the Many Worlds perspective, and the Penrose interpretation. These insights challenge us to explore human consciousness and innovation in economic organization. The discussion also brings in the principle of relational inter-subjectivity, emotion, and consciousness as a potential driver of human capital and value. In short, positive emotions can influence economic decision-making, as can negative emotions. These challenges stress the problem of human relational subjectivity, values, and technology as the tools to better understand the conflicts and potentials of human capital for New Economic Theory. The issue of value-analysis has both a descriptive and normative dimension. Both of these aspects raise important challenges

Moral calculations game theory, logic, and human frailty

CERN Document Server

Mérő, László

1998-01-01

Are people ever rational? Consider this: You auction off a one-dollar bill to the highest bidder, but you set the rules so that the second highest bidder also has to pay the amount of his last bid, even though he gets nothing. Would people ever enter such an auction? Not only do they, but according to Martin Shubik, the game's inventor, the average winning bid (for a dollar, remember) is $3.40. Many winners report that they bid so high only because their opponent "went completely crazy." This game lies at the intersection of three subjects of eternal fascination: human psychology, morality, and John von Neumann's game theory. Hungarian game-theorist Laszlo Mero introduces us to the basics of game theory, including such concepts as zero-sum games, Prisoner's Dilemma and the origins of altruism; shows how game theory is applicable to fields ranging from physics to politics; and explores the role of rational thinking in the context of many different kinds of thinking. This fascinating, urbane book will interest ...

Human brain evolution, theories of innovation, and lessons from the ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Biosciences; Volume 29; Issue 3. Human brain evolution, theories of innovation, and lessons from the history of technology. Alfred Gierer. Perspectives Volume 29 Issue 3 September 2004 pp 235-244. Fulltext. Click here to view fulltext PDF. Permanent link:

A Test of Evolutionary Policing Theory with Data from Human Societies

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Kümmerli, Rolf

2011-01-01

In social groups where relatedness among interacting individuals is low, cooperation can often only be maintained through mechanisms that repress competition among group members. Repression-of-competition mechanisms, such as policing and punishment, seem to be of particular importance in human societies, where cooperative interactions often occur among unrelated individuals. In line with this view, economic games have shown that the ability to punish defectors enforces cooperation among humans. Here, I examine a real-world example of a repression-of-competition system, the police institutions common to modern human societies. Specifically, I test evolutionary policing theory by comparing data on policing effort, per capita crime rate, and similarity (used as a proxy for genetic relatedness) among citizens across the 26 cantons of Switzerland. This comparison revealed full support for all three predictions of evolutionary policing theory. First, when controlling for policing efforts, crime rate correlated negatively with the similarity among citizens. This is in line with the prediction that high similarity results in higher levels of cooperative self-restraint (i.e. lower crime rates) because it aligns the interests of individuals. Second, policing effort correlated negatively with the similarity among citizens, supporting the prediction that more policing is required to enforce cooperation in low-similarity societies, where individuals' interests diverge most. Third, increased policing efforts were associated with reductions in crime rates, indicating that policing indeed enforces cooperation. These analyses strongly indicate that humans respond to cues of their social environment and adjust cheating and policing behaviour as predicted by evolutionary policing theory. PMID:21909429

A test of evolutionary policing theory with data from human societies.

Science.gov (United States)

Kümmerli, Rolf

2011-01-01

In social groups where relatedness among interacting individuals is low, cooperation can often only be maintained through mechanisms that repress competition among group members. Repression-of-competition mechanisms, such as policing and punishment, seem to be of particular importance in human societies, where cooperative interactions often occur among unrelated individuals. In line with this view, economic games have shown that the ability to punish defectors enforces cooperation among humans. Here, I examine a real-world example of a repression-of-competition system, the police institutions common to modern human societies. Specifically, I test evolutionary policing theory by comparing data on policing effort, per capita crime rate, and similarity (used as a proxy for genetic relatedness) among citizens across the 26 cantons of Switzerland. This comparison revealed full support for all three predictions of evolutionary policing theory. First, when controlling for policing efforts, crime rate correlated negatively with the similarity among citizens. This is in line with the prediction that high similarity results in higher levels of cooperative self-restraint (i.e. lower crime rates) because it aligns the interests of individuals. Second, policing effort correlated negatively with the similarity among citizens, supporting the prediction that more policing is required to enforce cooperation in low-similarity societies, where individuals' interests diverge most. Third, increased policing efforts were associated with reductions in crime rates, indicating that policing indeed enforces cooperation. These analyses strongly indicate that humans respond to cues of their social environment and adjust cheating and policing behaviour as predicted by evolutionary policing theory.

A test of evolutionary policing theory with data from human societies.

Directory of Open Access Journals (Sweden)

Rolf Kümmerli

Full Text Available In social groups where relatedness among interacting individuals is low, cooperation can often only be maintained through mechanisms that repress competition among group members. Repression-of-competition mechanisms, such as policing and punishment, seem to be of particular importance in human societies, where cooperative interactions often occur among unrelated individuals. In line with this view, economic games have shown that the ability to punish defectors enforces cooperation among humans. Here, I examine a real-world example of a repression-of-competition system, the police institutions common to modern human societies. Specifically, I test evolutionary policing theory by comparing data on policing effort, per capita crime rate, and similarity (used as a proxy for genetic relatedness among citizens across the 26 cantons of Switzerland. This comparison revealed full support for all three predictions of evolutionary policing theory. First, when controlling for policing efforts, crime rate correlated negatively with the similarity among citizens. This is in line with the prediction that high similarity results in higher levels of cooperative self-restraint (i.e. lower crime rates because it aligns the interests of individuals. Second, policing effort correlated negatively with the similarity among citizens, supporting the prediction that more policing is required to enforce cooperation in low-similarity societies, where individuals' interests diverge most. Third, increased policing efforts were associated with reductions in crime rates, indicating that policing indeed enforces cooperation. These analyses strongly indicate that humans respond to cues of their social environment and adjust cheating and policing behaviour as predicted by evolutionary policing theory.

Epileptic seizure propagation from the second somatic sensory area to the fronto-medial region, by insular redistribution. A case report and a connectome description

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Balogh Attila

2015-06-01

Full Text Available Introduction. The seizure propagation phenomenon by inducing remote symptoms brings several difficulties in finding the seizure onset and delineating the epileptic network which should be taken into consideration in epilepsy surgery. By demonstrating a difficult (MRI negative epilepsy surgery case explored with invasive presurgical evaluation we highlight the importance to recognise the secondary sensory area and to explore the the parieto-opercular-insular-medial frontal network in certain cases. A further conclusion is the consideration of the redistributory role of the insula as a special structure in the cerebral connectome, having a role in epileptic network organisation.

The CONNECT project

DEFF Research Database (Denmark)

Assaf, Yaniv; Alexander, Daniel C; Jones, Derek K

2013-01-01

Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper...... summarizes the project and describes the perspective of using micro-structural measures to study the connectome.......In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using...

Design for human factors (DfHF): a grounded theory for integrating human factors into production design processes.

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Village, Judy; Searcy, Cory; Salustri, Filipo; Patrick Neumann, W

2015-01-01

The 'design for human factors' grounded theory explains 'how' human factors (HF) went from a reactive, after-injury programme in safety, to being proactively integrated into each step of the production design process. In this longitudinal case study collaboration with engineers and HF Specialists in a large electronics manufacturer, qualitative data (e.g. meetings, interviews, observations and reflections) were analysed using a grounded theory methodology. The central tenet in the theory is that when HF Specialists acclimated to the engineering process, language and tools, and strategically aligned HF to the design and business goals of the organisation, HF became a means to improve business performance. This led to engineers 'pulling' HF Specialists onto their team. HF targets were adopted into engineering tools to communicate HF concerns quantitatively, drive continuous improvement, visibly demonstrate change and lead to benchmarking. Senior management held engineers accountable for HF as a key performance indicator, thus integrating HF into the production design process. Practitioner Summary: Research and practice lack explanations about how HF can be integrated early in design of production systems. This three-year case study and the theory derived demonstrate how ergonomists changed their focus to align with design and business goals to integrate HF into the design process.

The quartet theory of human emotions: An integrative and neurofunctional model.

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Koelsch, Stefan; Jacobs, Arthur M; Menninghaus, Winfried; Liebal, Katja; Klann-Delius, Gisela; von Scheve, Christian; Gebauer, Gunter

2015-06-01

Despite an explosion of research in the affective sciences during the last few decades, interdisciplinary theories of human emotions are lacking. Here we present a neurobiological theory of emotions that includes emotions which are uniquely human (such as complex moral emotions), considers the role of language for emotions, advances the understanding of neural correlates of attachment-related emotions, and integrates emotion theories from different disciplines. We propose that four classes of emotions originate from four neuroanatomically distinct cerebral systems. These emotional core systems constitute a quartet of affect systems: the brainstem-, diencephalon-, hippocampus-, and orbitofrontal-centred affect systems. The affect systems were increasingly differentiated during the course of evolution, and each of these systems generates a specific class of affects (e.g., ascending activation, pain/pleasure, attachment-related affects, and moral affects). The affect systems interact with each other, and activity of the affect systems has effects on - and interacts with - biological systems denoted here as emotional effector systems. These effector systems include motor systems (which produce actions, action tendencies, and motoric expression of emotion), peripheral physiological arousal, as well as attentional and memory systems. Activity of affect systems and effector systems is synthesized into an emotion percept (pre-verbal subjective feeling), which can be transformed (or reconfigured) into a symbolic code such as language. Moreover, conscious cognitive appraisal (involving rational thought, logic, and usually language) can regulate, modulate, and partly initiate, activity of affect systems and effector systems. Our emotion theory integrates psychological, neurobiological, sociological, anthropological, and psycholinguistic perspectives on emotions in an interdisciplinary manner, aiming to advance the understanding of human emotions and their neural correlates

The quartet theory of human emotions: An integrative and neurofunctional model

Science.gov (United States)

Koelsch, Stefan; Jacobs, Arthur M.; Menninghaus, Winfried; Liebal, Katja; Klann-Delius, Gisela; von Scheve, Christian; Gebauer, Gunter

2015-06-01

Despite an explosion of research in the affective sciences during the last few decades, interdisciplinary theories of human emotions are lacking. Here we present a neurobiological theory of emotions that includes emotions which are uniquely human (such as complex moral emotions), considers the role of language for emotions, advances the understanding of neural correlates of attachment-related emotions, and integrates emotion theories from different disciplines. We propose that four classes of emotions originate from four neuroanatomically distinct cerebral systems. These emotional core systems constitute a quartet of affect systems: the brainstem-, diencephalon-, hippocampus-, and orbitofrontal-centred affect systems. The affect systems were increasingly differentiated during the course of evolution, and each of these systems generates a specific class of affects (e.g., ascending activation, pain/pleasure, attachment-related affects, and moral affects). The affect systems interact with each other, and activity of the affect systems has effects on - and interacts with - biological systems denoted here as emotional effector systems. These effector systems include motor systems (which produce actions, action tendencies, and motoric expression of emotion), peripheral physiological arousal, as well as attentional and memory systems. Activity of affect systems and effector systems is synthesized into an emotion percept (pre-verbal subjective feeling), which can be transformed (or reconfigured) into a symbolic code such as language. Moreover, conscious cognitive appraisal (involving rational thought, logic, and usually language) can regulate, modulate, and partly initiate, activity of affect systems and effector systems. Our emotion theory integrates psychological, neurobiological, sociological, anthropological, and psycholinguistic perspectives on emotions in an interdisciplinary manner, aiming to advance the understanding of human emotions and their neural correlates.

Structure-Interaction Theory: Conceptual, Contextual and Strategic Influences on Human Communication

Directory of Open Access Journals (Sweden)

Стивен А Биби

2015-12-01

Full Text Available This paper addresses Structure-Interaction Theory (SIT, a theoretical framework that both describes communication messages as well as assists in making predictions about how human communication can be improved based on listener preferences for message structure or interaction. Communication messages may be characterized as existing on a continuum of structure-interaction. Communication structure is the inherent way information in a message is organized. A highly structured message is one in which the message is strategically organized using a planned arrangement of symbols to create meaning. Communication interaction is a way of viewing a message with give-and-take, less sustained “notes,” more change in note sequence and briefer notes. SIT seeks to provide a framework to assist communicators in appropriately adapting a message for maximum effectiveness. Although Structure-Interaction Theory newly articulated here, it is anchored in both classic ways of describing communication, such as rhetoric and dialectic (Aristotle, 1959, as well as more contemporary communication theories (Salem, 2012; Littlejohn & Foss, 2008. Specifically, the paper provides an overview of the theory and its conceptual assumptions, identifies how the theory can help explain and predict communication in several communication contexts (interpersonal, group, public communication, and suggests how SIT may help identify strategies to enhance human development. Structure-Interaction Theory is based on an assumption that a human communication message which is understood, achieves the intended effect of the communicator, and is ethical, requires an appropriate balance of two things: structure and interaction. Communication structure is the inherent way a message is constructed to provide a sustained direction to present information to another person. In linking structure and interaction to Aristotle’s description of messages, rhetoric is a more structured, sustained speech

Consumption as investment: The theory of human capital and human capital as ethos

Directory of Open Access Journals (Sweden)

Osvaldo Javier López-Ruiz

2009-12-01

Full Text Available This paper discusses the dilution of the conceptual border between “consumption” and “investment.” We argue that it is a key element for the understanding of capitalism in its current stage and the values guiding contemporary society. Some concepts created by Human Capital Theory – an economic theory from the 1960s – are widely viewed today as values that guide the behavior of individuals. This yields to a conceptual–axiological shift from consumption to investment that allows unusual forms of “delaying satisfaction by consuming now.” The diffuse area that is created between “consumption” and “investment” helps to understand how the Protestant work ethic is recreated as an “ethic of entrepreneurial work,” that is, of work understood in terms of “individual enterprise”.

What Is "Human" in Human Capital Theory? Marking a Transition from Industrial to Postindustrial Education

Science.gov (United States)

Peers, Chris

2015-01-01

This article addresses educational practice as a site for the development of human capital theory. The article considers metaphysical constructions that are broadly typical of educational thought, and shows how they are amenable to economic analysis. Using different Marxist and feminist methods, it discusses pedagogy and the family as kinds of…

A theory of social thermoregulation in human primates.

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IJzerman, Hans; Coan, James A; Wagemans, Fieke M A; Missler, Marjolein A; van Beest, Ilja; Lindenberg, Siegwart; Tops, Mattie

2015-01-01

Beyond breathing, the regulation of body temperature-thermoregulation-is one of the most pressing concerns for many animals. A dysregulated body temperature has dire consequences for survival and development. Despite the high frequency of social thermoregulation occurring across many species, little is known about the role of social thermoregulation in human (social) psychological functioning. We outline a theory of social thermoregulation and reconsider earlier research on people's expectations of their social world (i.e., attachment) and their prediction of the social world. We provide support and outline a research agenda that includes consequences for individual variation in self-regulatory strategies and capabilities. In our paper, we discuss physiological, neural, and social processes surrounding thermoregulation. Emphasizing social thermoregulation in particular, we appeal to the economy of action principle and the hierarchical organization of human thermoregulatory systems. We close with future directions of a crucial aspect of human functioning: the social regulation of body temperature.

Using experimental game theory to transit human values to ethical AI

OpenAIRE

Wang, Yijia; Wan, Yan; Wang, Zhijian

2017-01-01

Knowing the reflection of game theory and ethics, we develop a mathematical representation to bridge the gap between the concepts in moral philosophy (e.g., Kantian and Utilitarian) and AI ethics industry technology standard (e.g., IEEE P7000 standard series for Ethical AI). As an application, we demonstrate how human value can be obtained from the experimental game theory (e.g., trust game experiment) so as to build an ethical AI. Moreover, an approach to test the ethics (rightness or wrongn...

Consciousness, plasticity, and connectomics: the role of intersubjectivity in human cognition

DEFF Research Database (Denmark)

Allen, Micah Galen; Williams, Gary

2011-01-01

motivates philosophical and empirical hypotheses regarding the appropriate time-scale and function of neuroplastic adaptation, the relation of high and low-frequency neural activity to consciousness and cognitive plasticity, and the role of ritual social practices in neural development and cognitive...... take up our account of consciousness from the observation of radical cortical neuroplasticity in human development. Accordingly, we draw upon recent research on macroscopic neural networks, including the “default mode,” to illustrate cases in which an individual’s particular “connectome” is shaped...

Technological Innovation and Strategic Human Resource Management: Developing a Theory.

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Gattiker, Urs E.

Technological innovation affects the structure and content of jobs. Research indicates that there is a need for a theory of technological innovation and strategic human resource management considering several factors, such as an employee's beliefs about the effect of technological innovations on the quality of work life and work content.…

Sensitivity analysis of human brain structural network construction

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Kuang Wei

2017-12-01

Full Text Available Network neuroscience leverages diffusion-weighted magnetic resonance imaging and tractography to quantify structural connectivity of the human brain. However, scientists and practitioners lack a clear understanding of the effects of varying tractography parameters on the constructed structural networks. With diffusion images from the Human Connectome Project (HCP, we characterize how structural networks are impacted by the spatial resolution of brain atlases, total number of tractography streamlines, and grey matter dilation with various graph metrics. We demonstrate how injudicious combinations of highly refined brain parcellations and low numbers of streamlines may inadvertently lead to disconnected network models with isolated nodes. Furthermore, we provide solutions to significantly reduce the likelihood of generating disconnected networks. In addition, for different tractography parameters, we investigate the distributions of values taken by various graph metrics across the population of HCP subjects. Analyzing the ranks of individual subjects within the graph metric distributions, we find that the ranks of individuals are affected differently by atlas scale changes. Our work serves as a guideline for researchers to optimize the selection of tractography parameters and illustrates how biological characteristics of the brain derived in network neuroscience studies can be affected by the choice of atlas parcellation schemes. Diffusion tractography has been proven to be a promising noninvasive technique to study the network properties of the human brain. However, how various tractography and network construction parameters affect network properties has not been studied using a large cohort of high-quality data. We utilize data provided by the Human Connectome Project to characterize the changes to network properties induced by varying the brain parcellation atlas scales, the number of reconstructed tractography tracks, and the degree of grey

Categorial Compositionality: A Category Theory Explanation for the Systematicity of Human Cognition

OpenAIRE

Phillips, Steven; Wilson, William H.

2010-01-01

Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours) as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks) that do not account for systematicity. By analogy with the P...

The Valency Theory: The Human Bond From A New Psychoanalytic Perspective

OpenAIRE

Med Hafsi

2008-01-01

The present paper discusses some psychoanalytical conceptions concerning what links people to each other, or the human bond. Psychoanalysis, can be regarded as a science dealing basically with, although not directly, the human bond or link linking the person with his external and internal objects. The fact that this bond is in perpetualtransformation, and therefore can be apprehended from different angles has led to various psychoanalytical conceptions or theories which are more complementary...

A theory for aftercare of human trafficking survivors for nursing practice in low resource settings.

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Curran, R L; Naidoo, J R; Mchunu, G

2017-06-01

Research on aftercare for human trafficking survivors highlights the limited knowledge of the needs of survivors; the evaluation of current aftercare; and the process of recovery navigated by the survivor in aftercare (Oram et al., 2012; Locke, 2010; Hacker & Cohen, 2012). Furthermore there has been a transition in aftercare where the victim or survivor, who before was seen as a passive victim of circumstance of their life and in need of therapeutic intervention, is now seen as having an active role in their recovery, thus facilitating recovery (Hacker & Cohen, 2012). The need for a theory grounded in survivor's voices therefore motivated this grounded theory study underpinned by Freire's (1970) Pedagogy of the oppressed. The aim of the theory is to inform nursing care of human trafficking survivors in low resource settings. The findings elicit a theoretical model of the renewed self, and the conditions that facilitate this process in care of human trafficking survivors. The recommendations of this paper may improve the nursing care provided to human trafficking survivors and equip nurses and other health professionals with the knowledge and skills to promote the renewing of human trafficking survivors. Copyright © 2017 Elsevier Inc. All rights reserved.

Looking at the ICF and human communication through the lens of classification theory.

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Walsh, Regina

2011-08-01

This paper explores the insights that classification theory can provide about the application of the International Classification of Functioning, Disability and Health (ICF) to communication. It first considers the relationship between conceptual models and classification systems, highlighting that classification systems in speech-language pathology (SLP) have not historically been based on conceptual models of human communication. It then overviews the key concepts and criteria of classification theory. Applying classification theory to the ICF and communication raises a number of issues, some previously highlighted through clinical application. Six focus questions from classification theory are used to explore these issues, and to propose the creation of an ICF-related conceptual model of communicating for the field of communication disability, which would address some of the issues raised. Developing a conceptual model of communication for SLP purposes closely articulated with the ICF would foster productive intra-professional discourse, while at the same time allow the profession to continue to use the ICF for purposes in inter-disciplinary discourse. The paper concludes by suggesting the insights of classification theory can assist professionals to apply the ICF to communication with the necessary rigour, and to work further in developing a conceptual model of human communication.

Application of activity theory to analysis of human-related accidents: Method and case studies

International Nuclear Information System (INIS)

Yoon, Young Sik; Ham, Dong-Han; Yoon, Wan Chul

2016-01-01

This study proposes a new approach to human-related accident analysis based on activity theory. Most of the existing methods seem to be insufficient for comprehensive analysis of human activity-related contextual aspects of accidents when investigating the causes of human errors. Additionally, they identify causal factors and their interrelationships with a weak theoretical basis. We argue that activity theory offers useful concepts and insights to supplement existing methods. The proposed approach gives holistic contextual backgrounds for understanding and diagnosing human-related accidents. It also helps identify and organise causal factors in a consistent, systematic way. Two case studies in Korean nuclear power plants are presented to demonstrate the applicability of the proposed method. Human Factors Analysis and Classification System (HFACS) was also applied to the case studies. The results of using HFACS were then compared with those of using the proposed method. These case studies showed that the proposed approach could produce a meaningful set of human activity-related contextual factors, which cannot easily be obtained by using existing methods. It can be especially effective when analysts think it is important to diagnose accident situations with human activity-related contextual factors derived from a theoretically sound model and to identify accident-related contextual factors systematically. - Highlights: • This study proposes a new method for analysing human-related accidents. • The method was developed based on activity theory. • The concept of activity system model and contradiction was used in the method. • Two case studies in nuclear power plants are presented. • The method is helpful to consider causal factors systematically and comprehensively.

Human Rights in The Monotheistic Religions : Justification of Human Rights in the perspective of monotheistic religion according to Human Rights Theories

OpenAIRE

Ali, Sadaqat

2018-01-01

The discourse of human rights has been very prominent in the post-world wars which led various international organizations and institutes to generate awareness on this subject and pave a path for implementation of fundamental human rights in the world. Many theories have been coined and proliferated in the world to look the matter more seriously. The question mark on the role of religion in this regard has led the discussion sidelining divinely revealed monotheistic religions. Thus, religions...

Ising model with conserved magnetization on the human connectome: Implications on the relation structure-function in wakefulness and anesthesia

Science.gov (United States)

Stramaglia, S.; Pellicoro, M.; Angelini, L.; Amico, E.; Aerts, H.; Cortés, J. M.; Laureys, S.; Marinazzo, D.

2017-04-01

Dynamical models implemented on the large scale architecture of the human brain may shed light on how a function arises from the underlying structure. This is the case notably for simple abstract models, such as the Ising model. We compare the spin correlations of the Ising model and the empirical functional brain correlations, both at the single link level and at the modular level, and show that their match increases at the modular level in anesthesia, in line with recent results and theories. Moreover, we show that at the peak of the specific heat (the critical state), the spin correlations are minimally shaped by the underlying structural network, explaining how the best match between the structure and function is obtained at the onset of criticality, as previously observed. These findings confirm that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.

Small-world human brain networks: Perspectives and challenges.

Science.gov (United States)

Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

2017-06-01

Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fit for Practice: Analysis and Evaluation of Watson's Theory of Human Caring.

Science.gov (United States)

Pajnkihar, Majda; McKenna, Hugh P; Štiglic, Gregor; Vrbnjak, Dominika

2017-07-01

The aim of the authors of this paper is to analyze Watson's theory of human caring for its usefulness and worth in education, practice, and research. The reason for undertaking this analysis is to evaluate if Watson's theory would be useful for nursing in those countries where such theories were not an established part of the nursing curriculum. Furthermore, in some European countries, their political past or cultural influences led to an unquestioned adoption of the biomedical model. As their political culture changes, many social structures have had to be revisited, and for nursing, this has meant the introduction of theoretical reasoning, teaching, and practice.

Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

Science.gov (United States)

Vecchio, Fabrizio; Miraglia, Francesca; Rossini, Paolo Maria

2018-05-01

The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human "Connectome." Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task's performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

On the physical basis of a theory of human thermoregulation.

Science.gov (United States)

Iberall, A. S.; Schindler, A. M.

1973-01-01

Theoretical study of the physical factors which are responsible for thermoregulation in nude resting humans in a physical steady state. The behavior of oxidative metabolism, evaporative and convective thermal fluxes, fluid heat transfer, internal and surface temperatures, and evaporative phase transitions is studied by physiological/physical modeling techniques. The modeling is based on the theories that the body has a vital core with autothermoregulation, that the vital core contracts longitudinally, that the temperature of peripheral regions and extremities decreases towards the ambient, and that a significant portion of the evaporative heat may be lost underneath the skin. A theoretical basis is derived for a consistent modeling of steady-state thermoregulation on the basis of these theories.

A Two-Step Theory of the Evolution of Human Thinking

Directory of Open Access Journals (Sweden)

Satne Glenda

2016-03-01

Full Text Available Social accounts of objective content, like the one advanced by Tomasello (2014, are traditionally challenged by an ‘essential tension’ (Hutto and Satne 2015. The tension is the following: while sociality is deemed to be at the basis of thinking, in order to explain sociality, some form of thinking seems to be necessarily presupposed. In this contribution I analyse Tomasello’s two-step theory of the evolution of human thinking vis-à-vis this challenge. While his theory is in principle suited to address it, I claim that the specifics of the first step and the notion of perspective that infuse it are problematic in this regard. I end by briefly sketching an alternative.

Educational Mismatches and Earnings: Extensions of Occupational Mobility Theory and Evidence of Human Capital Depreciation

Science.gov (United States)

Rubb, Stephen

2006-01-01

Using a human capital theory framework, this study examines the impact of educational mismatches on earnings and occupational mobility. Occupational mobility theory suggests that overeducated workers observe greater upward occupational mobility and undereducated workers observe lower upward occupational mobility. By extension, this leads to…

Categorial compositionality: a category theory explanation for the systematicity of human cognition.

Directory of Open Access Journals (Sweden)

Steven Phillips

Full Text Available Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks that do not account for systematicity. By analogy with the Ptolemaic (i.e. geocentric theory of planetary motion, although either theory can be made to be consistent with the data, both nonetheless fail to fully explain it. Category theory, a branch of mathematics, provides an alternative explanation based on the formal concept of adjunction, which relates a pair of structure-preserving maps, called functors. A functor generalizes the notion of a map between representational states to include a map between state transformations (or processes. In a formal sense, systematicity is a necessary consequence of a higher-order theory of cognitive architecture, in contrast to the first-order theories derived from Classicism or Connectionism. Category theory offers a re-conceptualization for cognitive science, analogous to the one that Copernicus provided for astronomy, where representational states are no longer the center of the cognitive universe--replaced by the relationships between the maps that transform them.

Categorial compositionality: a category theory explanation for the systematicity of human cognition.

Science.gov (United States)

Phillips, Steven; Wilson, William H

2010-07-22

Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours) as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks) that do not account for systematicity. By analogy with the Ptolemaic (i.e. geocentric) theory of planetary motion, although either theory can be made to be consistent with the data, both nonetheless fail to fully explain it. Category theory, a branch of mathematics, provides an alternative explanation based on the formal concept of adjunction, which relates a pair of structure-preserving maps, called functors. A functor generalizes the notion of a map between representational states to include a map between state transformations (or processes). In a formal sense, systematicity is a necessary consequence of a higher-order theory of cognitive architecture, in contrast to the first-order theories derived from Classicism or Connectionism. Category theory offers a re-conceptualization for cognitive science, analogous to the one that Copernicus provided for astronomy, where representational states are no longer the center of the cognitive universe--replaced by the relationships between the maps that transform them.

CoCoMac 2.0 and the future of tract-tracing databases

Science.gov (United States)

Bakker, Rembrandt; Wachtler, Thomas; Diesmann, Markus

2012-01-01

The CoCoMac database contains the results of several hundred published axonal tract-tracing studies in the macaque monkey brain. The combined results are used for constructing the macaque macro-connectome. Here we discuss the redevelopment of CoCoMac and compare it to six connectome-related projects: two online resources that provide full access to raw tracing data in rodents, a connectome viewer for advanced 3D graphics, a partial but highly detailed rat connectome, a brain data management system that generates custom connectivity matrices, and a software package that covers the complete pipeline from connectivity data to large-scale brain simulations. The second edition of CoCoMac features many enhancements over the original. For example, a search wizard is provided for full access to all tables and their nested dependencies. Connectivity matrices can be computed on demand in a user-selected nomenclature. A new data entry system is available as a preview, and is to become a generic solution for community-driven data entry in manually collated databases. We conclude with the question whether neuronal tracing will remain the gold standard to uncover the wiring of brains, thereby highlighting developments in human connectome construction, tracer substances, polarized light imaging, and serial block-face scanning electron microscopy. PMID:23293600

CoCoMac 2.0 and the future of tract-tracing databases

Directory of Open Access Journals (Sweden)

Rembrandt eBakker

2012-12-01

Full Text Available The CoCoMac database contains the results of published axonal tract-tracing studies in the macaque brain. The combined data are used to construct the macaque macro-connectome. We discuss the redevelopment of CoCoMac and compare it to six connectome-related projects: two resources that provide online access to raw tracing data in rodents, a connectome viewer for advanced 3d graphics, a partial but highly detailed rat connectome, a brain data management system that generates custom connectivity matrices, and a software package that covers the complete pipeline from connectivity data to large scale brain simulations.The 2nd edition of CoCoMac features many enhancements over the original. For example, a search wizard is provided for full access to all tables. Connectivity matrices are computed on demand in a user selected nomenclature. An online data entry system is available as a preview, and is to become a generic solution for community-driven manual data entry.We end with the question whether tract-tracing will remain the gold standard to uncover the wiring of brains, thereby mentioning developments in human connectome construction, tracer substances, polarized light imaging and serial block face scanning electron microscopy.

CoCoMac 2.0 and the future of tract-tracing databases.

Science.gov (United States)

Bakker, Rembrandt; Wachtler, Thomas; Diesmann, Markus

2012-01-01

The CoCoMac database contains the results of several hundred published axonal tract-tracing studies in the macaque monkey brain. The combined results are used for constructing the macaque macro-connectome. Here we discuss the redevelopment of CoCoMac and compare it to six connectome-related projects: two online resources that provide full access to raw tracing data in rodents, a connectome viewer for advanced 3D graphics, a partial but highly detailed rat connectome, a brain data management system that generates custom connectivity matrices, and a software package that covers the complete pipeline from connectivity data to large-scale brain simulations. The second edition of CoCoMac features many enhancements over the original. For example, a search wizard is provided for full access to all tables and their nested dependencies. Connectivity matrices can be computed on demand in a user-selected nomenclature. A new data entry system is available as a preview, and is to become a generic solution for community-driven data entry in manually collated databases. We conclude with the question whether neuronal tracing will remain the gold standard to uncover the wiring of brains, thereby highlighting developments in human connectome construction, tracer substances, polarized light imaging, and serial block-face scanning electron microscopy.

Is the social brain theory applicable to human individual differences? Relationship between sociability personality dimension and brain size.

Science.gov (United States)

Horváth, Klára; Martos, János; Mihalik, Béla; Bódizs, Róbert

2011-06-17

Our study intends to examine whether the social brain theory is applicable to human individual differences. According to the social brain theory primates have larger brains as it could be expected from their body sizes due to the adaptation to a more complex social life. Regarding humans there were few studies about the relationship between theory of mind and frontal and temporal brain lobes. We hypothesized that these brain lobes, as well as the whole cerebrum and neocortex are in connection with the Sociability personality dimension that is associated with individuals' social lives. Our findings support this hypothesis as Sociability correlated positively with the examined brain structures if we control the effects of body size differences and age. These results suggest that the social brain theory can be extended to human interindividual differences and they have some implications to personality psychology too.

Why We Do What We Do: A Biopsychosocial Theory of Human Motivation.

Science.gov (United States)

Gove, Walter R.

1994-01-01

Outlines a theory of human motivation that focuses on the unpredictability of life, innate and noninnate differences in individual characteristics, individual responsibility for actions, importance of a meaningful life, intrinsic physiologic rewards of behavior, gender differences in behavior, adult psychological maturation, and limitations of the…

The quantum theory of time, the block universe, and human experience.

Science.gov (United States)

Vaccaro, Joan A

2018-07-13

Advances in our understanding of the physical universe have dramatically affected how we view ourselves. Right at the core of all modern thinking about the universe is the assumption that dynamics is an elemental feature that exists without question. However, ongoing research into the quantum nature of time is challenging this view: my recently introduced quantum theory of time suggests that dynamics may be a phenomenological consequence of a fundamental violation of time reversal symmetry. I show here that there is consistency between the new theory and the block universe view. I also discuss the new theory in relation to the human experience of existing in the present moment, able to reflect on the past and contemplate a future that is yet to happen.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Authors.

Human error theory: relevance to nurse management.

Science.gov (United States)

Armitage, Gerry

2009-03-01

Describe, discuss and critically appraise human error theory and consider its relevance for nurse managers. Healthcare errors are a persistent threat to patient safety. Effective risk management and clinical governance depends on understanding the nature of error. This paper draws upon a wide literature from published works, largely from the field of cognitive psychology and human factors. Although the content of this paper is pertinent to any healthcare professional; it is written primarily for nurse managers. Error is inevitable. Causation is often attributed to individuals, yet causation in complex environments such as healthcare is predominantly multi-factorial. Individual performance is affected by the tendency to develop prepacked solutions and attention deficits, which can in turn be related to local conditions and systems or latent failures. Blame is often inappropriate. Defences should be constructed in the light of these considerations and to promote error wisdom and organizational resilience. Managing and learning from error is seen as a priority in the British National Health Service (NHS), this can be better achieved with an understanding of the roots, nature and consequences of error. Such an understanding can provide a helpful framework for a range of risk management activities.

Human sensorimotor communication: a theory of signaling in online social interactions.

Science.gov (United States)

Pezzulo, Giovanni; Donnarumma, Francesco; Dindo, Haris

2013-01-01

Although the importance of communication is recognized in several disciplines, it is rarely studied in the context of online social interactions and joint actions. During online joint actions, language and gesture are often insufficient and humans typically use non-verbal, sensorimotor forms of communication to send coordination signals. For example, when playing volleyball, an athlete can exaggerate her movements to signal her intentions to her teammates (say, a pass to the right) or to feint an adversary. Similarly, a person who is transporting a table together with a co-actor can push the table in a certain direction to signal where and when he intends to place it. Other examples of "signaling" are over-articulating in noisy environments and over-emphasizing vowels in child-directed speech. In all these examples, humans intentionally modify their action kinematics to make their goals easier to disambiguate. At the moment no formal theory exists of these forms of sensorimotor communication and signaling. We present one such theory that describes signaling as a combination of a pragmatic and a communicative action, and explains how it simplifies coordination in online social interactions. We cast signaling within a "joint action optimization" framework in which co-actors optimize the success of their interaction and joint goals rather than only their part of the joint action. The decision of whether and how much to signal requires solving a trade-off between the costs of modifying one's behavior and the benefits in terms of interaction success. Signaling is thus an intentional strategy that supports social interactions; it acts in concert with automatic mechanisms of resonance, prediction, and imitation, especially when the context makes actions and intentions ambiguous and difficult to read. Our theory suggests that communication dynamics should be studied within theories of coordination and interaction rather than only in terms of the maximization of information

Human sensorimotor communication: a theory of signaling in online social interactions.

Directory of Open Access Journals (Sweden)

Giovanni Pezzulo

Full Text Available Although the importance of communication is recognized in several disciplines, it is rarely studied in the context of online social interactions and joint actions. During online joint actions, language and gesture are often insufficient and humans typically use non-verbal, sensorimotor forms of communication to send coordination signals. For example, when playing volleyball, an athlete can exaggerate her movements to signal her intentions to her teammates (say, a pass to the right or to feint an adversary. Similarly, a person who is transporting a table together with a co-actor can push the table in a certain direction to signal where and when he intends to place it. Other examples of "signaling" are over-articulating in noisy environments and over-emphasizing vowels in child-directed speech. In all these examples, humans intentionally modify their action kinematics to make their goals easier to disambiguate. At the moment no formal theory exists of these forms of sensorimotor communication and signaling. We present one such theory that describes signaling as a combination of a pragmatic and a communicative action, and explains how it simplifies coordination in online social interactions. We cast signaling within a "joint action optimization" framework in which co-actors optimize the success of their interaction and joint goals rather than only their part of the joint action. The decision of whether and how much to signal requires solving a trade-off between the costs of modifying one's behavior and the benefits in terms of interaction success. Signaling is thus an intentional strategy that supports social interactions; it acts in concert with automatic mechanisms of resonance, prediction, and imitation, especially when the context makes actions and intentions ambiguous and difficult to read. Our theory suggests that communication dynamics should be studied within theories of coordination and interaction rather than only in terms of the

The CNS connectome of a tadpole larva of Ciona intestinalis (L.) highlights sidedness in the brain of a chordate sibling.

Science.gov (United States)

Ryan, Kerrianne; Lu, Zhiyuan; Meinertzhagen, Ian A

2016-12-06

Left-right asymmetries in brains are usually minor or cryptic. We report brain asymmetries in the tiny, dorsal tubular nervous system of the ascidian tadpole larva, Ciona intestinalis . Chordate in body plan and development, the larva provides an outstanding example of brain asymmetry. Although early neural development is well studied, detailed cellular organization of the swimming larva's CNS remains unreported. Using serial-section EM we document the synaptic connectome of the larva's 177 CNS neurons. These formed 6618 synapses including 1772 neuromuscular junctions, augmented by 1206 gap junctions. Neurons are unipolar with at most a single dendrite, and few synapses. Some synapses are unpolarised, others form reciprocal or serial motifs; 922 were polyadic. Axo-axonal synapses predominate. Most neurons have ciliary organelles, and many features lack structural specialization. Despite equal cell numbers on both sides, neuron identities and pathways differ left/right. Brain vesicle asymmetries include a right ocellus and left coronet cells.

The Life Mission Theory VI. A Theory for the Human Character: Healing with Holistic Medicine Through Recovery of Character and Purpose of Life

Directory of Open Access Journals (Sweden)

Søren Ventegodt

2004-01-01

Full Text Available The human character can be understood as an extension of the life mission or purpose of life, and explained as the primary tool of a person to impact others and express the purpose of life. Repression of the human character makes it impossible for a person to realize his personal mission in life and, therefore, is one of the primary causes of self-repression resulting in poor quality of life, health, and ability. From Hippocrates to Hahnemann, repression of physical, mental, and spiritual character can be seen as the prime cause of disease, while recovery of character has been the primary intention of the treatment. In this paper, human character is explained as an intersubjective aspect of consciousness with the ability to influence the consciousness of another person directly. To understand consciousness, we reintroduce the seven-ray theory of consciousness explaining consciousness in accordance with a fractal ontology with a bifurcation number of seven (the numbers four to ten work almost as well. A case report on a female, aged 35 years, with severe hormonal disturbances, diagnosed with extremely early menopause, is presented and treated according to the theory of holistic existential healing (the holistic process theory of healing. After recovery of her character and purpose of life, her quality of life dramatically improved and hormonal status normalized. We believe that the recovery of human character and purpose of life was the central intention of Hippocrates and thus the original essence of western medicine. Interestingly, there are strong parallels to the peyote medicine of the Native Americans, the African Sangomas, the Australian Aboriginal healers, and the old Nordic medicine. The recovery of human character was also the intention of Hahnemann's homeopathy. We believe that we are at the core of consciousness-based medicine, as recovery of purpose of life and human character has been practiced as medicine in most human cultures

Quantum decision theory as quantum theory of measurement

International Nuclear Information System (INIS)

Yukalov, V.I.; Sornette, D.

2008-01-01

We present a general theory of quantum information processing devices, that can be applied to human decision makers, to atomic multimode registers, or to molecular high-spin registers. Our quantum decision theory is a generalization of the quantum theory of measurement, endowed with an action ring, a prospect lattice and a probability operator measure. The algebra of probability operators plays the role of the algebra of local observables. Because of the composite nature of prospects and of the entangling properties of the probability operators, quantum interference terms appear, which make actions noncommutative and the prospect probabilities nonadditive. The theory provides the basis for explaining a variety of paradoxes typical of the application of classical utility theory to real human decision making. The principal advantage of our approach is that it is formulated as a self-consistent mathematical theory, which allows us to explain not just one effect but actually all known paradoxes in human decision making. Being general, the approach can serve as a tool for characterizing quantum information processing by means of atomic, molecular, and condensed-matter systems

Application of human error theory in case analysis of wrong procedures.

Science.gov (United States)

Duthie, Elizabeth A

2010-06-01

The goal of this study was to contribute to the emerging body of literature about the role of human behaviors and cognitive processes in the commission of wrong procedures. Case analysis of 5 wrong procedures in operative and nonoperative settings using James Reason's human error theory was performed. The case analysis showed that cognitive underspecification, cognitive flips, automode processing, and skill-based errors were contributory to wrong procedures. Wrong-site procedures accounted for the preponderance of the cases. Front-line supervisory staff used corrective actions that focused on the performance of the individual without taking into account cognitive factors. System fixes using human cognition concepts have a greater chance of achieving sustainable safety outcomes than those that are based on the traditional approach of counseling, education, and disciplinary action for staff.

The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets.

Science.gov (United States)

Anderson, J R; Mohammed, S; Grimm, B; Jones, B W; Koshevoy, P; Tasdizen, T; Whitaker, R; Marc, R E

2011-01-01

Modern microscope automation permits the collection of vast amounts of continuous anatomical imagery in both two and three dimensions. These large data sets present significant challenges for data storage, access, viewing, annotation and analysis. The cost and overhead of collecting and storing the data can be extremely high. Large data sets quickly exceed an individual's capability for timely analysis and present challenges in efficiently applying transforms, if needed. Finally annotated anatomical data sets can represent a significant investment of resources and should be easily accessible to the scientific community. The Viking application was our solution created to view and annotate a 16.5 TB ultrastructural retinal connectome volume and we demonstrate its utility in reconstructing neural networks for a distinctive retinal amacrine cell class. Viking has several key features. (1) It works over the internet using HTTP and supports many concurrent users limited only by hardware. (2) It supports a multi-user, collaborative annotation strategy. (3) It cleanly demarcates viewing and analysis from data collection and hosting. (4) It is capable of applying transformations in real-time. (5) It has an easily extensible user interface, allowing addition of specialized modules without rewriting the viewer. © 2010 The Authors Journal of Microscopy © 2010 The Royal Microscopical Society.

Human emotion in the brain and the body: Why language matters. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

Science.gov (United States)

Herbert, Cornelia

2015-06-01

What is an Emotion? This question has fascinated scientific research since William James. Despite the fact that a consensus has been reached about the biological origin of emotions, uniquely human aspects of emotions are still poorly understood. One of these blind spots concerns the relationship between emotion and human language. Historically, many theories imply a duality between emotions on the one hand and cognitive functions such as language on the other hand. Especially for symbolic forms of written language and word processing, it has been assumed that semantic information would bear no relation to bodily, affective, or sensorimotor processing (for an overview see Ref. [1]). The Quartet Theory proposed by Koelsch and colleagues [2] could provide a solution to this problem. It offers a novel, integrative neurofunctional model of human emotions which considers language and emotion as closely related. Crucially, language - be it spoken or written - is assumed to "regulate, modulate, and partly initiate" activity in core affective brain systems in accord with physical needs and individual concerns [cf. page 34, line 995]. In this regard, the Quartet Theory combines assumptions from earlier bioinformational theories of emotions [3], contemporary theories of embodied cognition [4], and appraisal theories such as the Component Process Model [5] into one framework, thereby providing a holistic model for the neuroscientific investigation of human emotion processing at the interface of emotion and cognition, mind and body.

Using Multiattribute Utility Theory as a Priority-Setting Tool in Human Services Planning.

Science.gov (United States)

Camasso, Michael J.; Dick, Janet

1993-01-01

The feasibility of applying multiattribute utility theory to the needs assessment and priority-setting activities of human services planning councils was studied in Essex County (New Jersey). Decision-making and information filtering processes are explored in the context of community planning. (SLD)

Seeing More Than Human: Autism and Anthropomorphic Theory of Mind

Directory of Open Access Journals (Sweden)

Gray Atherton

2018-04-01

Full Text Available Theory of mind (ToM is defined as the process of taking another’s perspective. Anthropomorphism can be seen as the extension of ToM to non-human entities. This review examines the literature concerning ToM and anthropomorphism in relation to individuals with Autism Spectrum Disorder (ASD, specifically addressing the questions of how and why those on the spectrum both show an increased interest for anthropomorphism and may even show improved ToM abilities when judging the mental states of anthropomorphic characters. This review highlights that while individuals with ASD traditionally show deficits on a wide range of ToM tests, such as recognizing facial emotions, such ToM deficits may be ameliorated if the stimuli presented is cartoon or animal-like rather than in human form. Individuals with ASD show a greater interest in anthropomorphic characters and process the features of these characters using methods typically reserved for human stimuli. Personal accounts of individuals with ASD also suggest they may identify more closely with animals than other humans. It is shown how the social motivations hypothesized to underlie the anthropomorphizing of non-human targets may lead those on the spectrum to seek social connections and therefore gain ToM experience and expertise amongst unlikely sources.

A grounded theory of faculty's use of humanization to create online course climate.

Science.gov (United States)

Cox-Davenport, Rebecca A

2014-03-01

The purpose of this research was to study the way faculty establish course social presence in an online course. The community of inquiry model by Garrison, Anderson, and Archer distinguished the area of social presence as an important component of online learning, and this study sought to understand how faculty perceive and create social presence in their online classroom. By employing a grounded theory approach, a substantive theory was developed to explain the way in which faculty create and maintain an online course climate. The sample consisted of 10 nursing faculty teaching various master's in nursing courses. Through a rigorous qualitative process using nursing faculty interviews and online course analysis, humanization was found to be the core category in setting online course climate. Faculty's efforts to humanize the climate lead each member of the community to view the other members as real, thereby enabling the establishment of online social presence.

The Contribution of the Human Development Index Literacy Theory to the Debate on Literacy and Development

Science.gov (United States)

Biao, Idowu; Mogotsi, Kebadire; Maruatona, Tonic; Raditloaneng, Wapula; Tladi, Flora; Chawawa, Morgan; Kheru, Obakeng

2014-01-01

The Human Development Index Literacy (HDIL) theory was developed in 2011 to eliminate or minimise the negative impact of issues underlying the failure of previous literacy programmes in promoting socio-economic development. This theory was tested for the first time between July 2013 and February 2014 in two rural communities of Botswana. A…

Historicizing affordance theory

DEFF Research Database (Denmark)

Pedersen, Sofie; Bang, Jytte Susanne

2017-01-01

The aim of this article is to discuss how mutually enriching points from both affordance theory and cultural-historical activity theory can promote theoretical ideas which may prove useful as analytical tools for the study of human life and human development. There are two issues that need...... to be overcome in order to explore the potentials of James Gibson’s affordance theory: it does not sufficiently theorize (a) development and (b) society. We claim that Gibson’s affordance theory still needs to be brought beyond “the axiom of immediacy.” Ambivalences in Gibson’s affordance theory...... societal character of affordance theory....

Graph theory reveals dysconnected hubs in 22q11DS and altered nodal efficiency in patients with hallucinations

Directory of Open Access Journals (Sweden)

Marie-Christine eOttet

2013-09-01

Full Text Available Schizophrenia is postulated to be the prototypical dysconnection disorder, in which hallucinations are the core symptom. Due to high heterogeneity in methodology across studies and the clinical phenotype, it remains unclear whether the structural brain dysconnection is global or focal and if clinical symptoms result from this dysconnection. In the present work, we attempt to clarify this issue by studying a population considered as a homogeneous genetic sub-type of schizophrenia, namely the 22q11.2 deletion syndrome (22q11.2DS. Cerebral MRIs were acquired for 46 patients and 48 age and gender matched controls (aged 6 to 26, respectively mean age = 15.20 ± 4.53 and 15.28 ± 4.35 years old. Using the Connectome mapper pipeline (connectomics.org that combines structural and diffusion MRI, we created a whole brain network for each individual. The graph theory was used to quantify the global and local properties in the brain network organization for each participant. A global degree loss of 6% was found in patients’ network along with an increased Characteristic Path Length. After identifying and comparing hubs, a significant loss of degree in patients’ hubs was found in 58% of them. Based on Allen’s brain network model for hallucinations, we explored the association between local efficiency and symptom severity. Negative correlations were found in the Broca’s area (p<0.004, the Wernicke area (p<0.023 and a positive correlation was found in the dorsolateral prefrontal cortex (DLPFC (p<0.014. In line with the dysconnection findings in schizophrenia, our results provide preliminary evidence for a targeted alteration in the brain network hubs’organisation in individuals with a genetic risk for schizophrenia. The study of specific disorganization in language, speech and thought regulation networks sharing similar network properties may help to understand their role in the hallucination mechanism.

Neutral Theory: From Complex Population History to Natural Selection and Sociocultural Phenomena in Human Populations.

Science.gov (United States)

Austerlitz, Frédéric; Heyer, Evelyne

2018-06-01

Here, we present a synthetic view on how Kimura's Neutral theory has helped us gaining insight on the different evolutionary forces that shape human evolution. We put this perspective in the frame of recent emerging challenges: the use of whole genome data for reconstructing population histories, natural selection on complex polygenic traits, and integrating cultural processes in human evolution.

Exploring agency beyond humans: the compatibility of Actor-Network Theory (ANT and resilience thinking

Directory of Open Access Journals (Sweden)

Angga Dwiartama

2014-09-01

Full Text Available At first glance, the compatibility of social theory and resilience thinking is not entirely evident, in part because the ontology of the former is rooted in social interactions among human beings rather than ecological process. Despite this difference, resilience thinking engages with particular aspects of social organization that have generated intense debates within social science, namely the role of humans as integral elements of social-ecological systems and the processes through which given social structures (including material relations are either maintained or transformed. Among social theoretical approaches, Actor-Network Theory (ANT is noted for its distinctive approach to these aspects. ANT proposes that human and nonhuman components (both referred to as actants have the same capacity to influence the development of social-ecological systems (represented as actor-networks by enacting relations and enrolling other actors. We explore the notion of agency that is employed in resilience thinking and ANT in order to extend our understandings of human-environment relationships through complementary insights from each approach. The discussion is illustrated by reference to ongoing assessment of resilience as it is experienced and expressed in two distinctive agricultural production systems: Indonesian rice and New Zealand kiwifruit. We conclude by establishing the potential for ANT to provide more profound theoretical conceptualizations of agency, both human and nonhuman, in analyses of social ecological systems.

Interactional nursing - a practice-theory in the dynamic field between the natural, human and social sciences

DEFF Research Database (Denmark)

Scheel, Merry Elisabeth; Pedersen, Birthe D.; Rosenkrands, Vibeke

2008-01-01

Nursing is often described from the point of view of either the natural or the human sciences. In contrast to this, the value foundation in Interactional nursing practice is understood from the point of view of the natural sciences as well as that of the human and social sciences. This article...... presents many-faceted practice-theory of nursing, which is situated in the dynamic field between these three sciences. The focus of the theory is on interaction and practice resulting in a caring practice. Here practice is based on Taylor's and MacIntyre's interpretation of this concept. Action in nursing...... is based on Habermas' three varied modes of action seen in the light of an understanding of the world as a system world and a life world. Nursing as an interactional practice-theory is presented with examples of interpretative nursing science, seen in the ethical action-oriented, socio-cultural framework...

Human Capital, (Human) Capabilities and Higher Education

Science.gov (United States)

Le Grange, L.

2011-01-01

In this article I initiate a debate into the (de)merits of human capital theory and human capability theory and discuss implications of the debate for higher education. Human capital theory holds that economic growth depends on investment in education and that economic growth is the basis for improving the quality of human life. Human capable…

Past and future corollaries of theories on causes of metabolic syndrome and obesity related co-morbidities part 2: a composite unifying theory review of human-specific co-adaptations to brain energy consumption.

Science.gov (United States)

McGill, Anne-Thea

2014-01-01

Metabolic syndrome (MetS) predicts type II diabetes mellitus (TIIDM), cardiovascular disease (CVD) and cancer, and their rates have escalated over the last few decades. Obesity related co-morbidities also overlap the concept of the metabolic syndrome (MetS). However, understanding of the syndrome's underlying causes may have been misapprehended. The current paper follows on from a theory review by McGill, A-T in Archives of Public Health, 72: 30. This accompanying paper utilises research on human evolution and new biochemistry to theorise on why MetS and obesity arise and how they affect the population. The basis of this composite unifying theory is that the proportionately large, energy-demanding human brain may have driven co-adaptive mechanisms to provide, or conserve, energy for the brain. A 'dual system' is proposed. 1) The enlarged, complex cortico-limbic-striatal system increases dietary energy by developing strong neural self-reward/motivation pathways for the acquisition of energy dense food, and (2) the nuclear factor-erythroid 2-related factor 2 (NRF2) cellular protection system amplifies antioxidant, antitoxicant and repair activity by employing plant chemicals. In humans who consume a nutritious diet, the NRF2 system has become highly energy efficient. Other relevant human-specific co-adaptations are explored. In order to 'test' this composite unifying theory it is important to show that the hypothesis and sub-theories pertain throughout the whole of human evolution and history up till the current era. Corollaries of the composite unifying theory of MetS are examined with respect to past under-nutrition and malnutrition since agriculture began 10,000 years ago. The effects of man-made pollutants on degenerative change are examined. Projections are then made from current to future patterns on the state of 'insufficient micronutrient and/or unbalanced high energy malnutrition with central obesity and metabolic dysregulation' or 'malnubesity'. Forecasts

Theory versus practice in the human factors and ergonomics discipline: Trends in journal publications from 1960 to 2010.

Science.gov (United States)

Chung, Amy Z Q; Williamson, Ann

2018-01-01

The research-practice gap has been highlighted as a barrier to effective practice in human factors and ergonomics (HFE). There is also evidence of a theory-research gap that may be limiting the scientific evidence base of HFE. The purpose of this study was to examine trends in journal publications, especially relating to the research-practice gap and the involvement of theory over time. A content analysis was conducted on 425 journal articles published in Human Factors, Ergonomics, and Applied Ergonomics from 1960 to 2010. Results showed evidence of growth in applied research with increasing collaborative research between research and industry, larger research teams, and more empirical research-especially on applied problems. While there has been a corresponding increase in the involvement of theory in HFE publications, around half of the publications failed to acknowledge theory. This calls into question whether the HFE discipline may be missing the benefits of theory to guide research and subsequent practice, and to enhance the development of new ideas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network.

Science.gov (United States)

Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M; Jack, Clifford R; Weiner, Michael W; Bernstein, Matt A; Thompson, Paul M

2015-08-01

Diffusion imaging can assess the white matter connections within the brain, revealing how neural pathways break down in Alzheimer's disease (AD). We analyzed 3-Tesla whole-brain diffusion-weighted images from 202 participants scanned by the Alzheimer's Disease Neuroimaging Initiative-50 healthy controls, 110 with mild cognitive impairment (MCI) and 42 AD patients. From whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We tested whether AD disrupts the "rich club" - a network property where high-degree network nodes are more interconnected than expected by chance. We calculated the rich club properties at a range of degree thresholds, as well as other network topology measures including global degree, clustering coefficient, path length, and efficiency. Network disruptions predominated in the low-degree regions of the connectome in patients, relative to controls. The other metrics also showed alterations, suggesting a distinctive pattern of disruption in AD, less pronounced in MCI, targeting global brain connectivity, and focusing on more remotely connected nodes rather than the central core of the network. AD involves severely reduced structural connectivity; our step-wise rich club coefficients analyze points to disruptions predominantly in the peripheral network components; other modalities of data are needed to know if this indicates impaired communication among non rich club regions. The highly connected core was relatively preserved, offering new evidence on the neural basis of progressive risk for cognitive decline. © 2015 Wiley Periodicals, Inc.

The Relationship Between Postsecondary Education and Skill: Comparing Credentialism with Human Capital Theory

Science.gov (United States)

Walters, David

2004-01-01

This paper assesses the importance of the credential requirements used by employers to attract graduates who will use their education on the job. The framework of this study is embedded within the theoretical debates between proponents of the credentialist and human capital theories of education. Past research related to these debates has focused…

Using human error theory to explore the supply of non-prescription medicines from community pharmacies.

Science.gov (United States)

Watson, M C; Bond, C M; Johnston, M; Mearns, K

2006-08-01

The importance of theory in underpinning interventions to promote effective professional practice is gaining recognition. The Medical Research Council framework for complex interventions has assisted in promoting awareness and adoption of theory into study design. Human error theory has previously been used by high risk industries but its relevance to healthcare settings and patient safety requires further investigation. This study used this theory as a framework to explore non-prescription medicine supply from community pharmacies. The relevance to other healthcare settings and behaviours is discussed. A 25% random sample was made of 364 observed consultations for non-prescription medicines. Each of the 91 consultations was assessed by two groups: a consensus group (stage 1) to identify common problems with the consultation process, and an expert group (stages 2 and 3) to apply human error theory to these consultations. Paired assessors (most of whom were pharmacists) categorised the perceived problems occurring in each consultation (stage 1). During stage 2 paired assessors from an expert group (comprising patient safety experts, community pharmacists and psychologists) considered whether each consultation was compliant with professional guidelines for the supply of pharmacy medicines. Each non-compliant consultation identified during stage 2 was then categorised as a slip/lapse, mistake, or violation using human error theory (stage 3). During stage 1 most consultations (n = 75, 83%) were deemed deficient in information exchange. At stage 2, paired assessors varied in attributing non-compliance to specific error types. Where agreement was achieved, the error type most often selected was "violation" (n = 27, 51.9%, stage 3). Consultations involving product requests were less likely to be guideline compliant than symptom presentations (OR 0.30, 95% CI 0.10 to 0.95, p = 0.05). The large proportion of consultations classified as violations suggests that either

Documenting genomics: Applying archival theory to preserving the records of the Human Genome Project.

Science.gov (United States)

Shaw, Jennifer

2016-02-01

The Human Genome Archive Project (HGAP) aimed to preserve the documentary heritage of the UK's contribution to the Human Genome Project (HGP) by using archival theory to develop a suitable methodology for capturing the results of modern, collaborative science. After assessing past projects and different archival theories, the HGAP used an approach based on the theory of documentation strategy to try to capture the records of a scientific project that had an influence beyond the purely scientific sphere. The HGAP was an archival survey that ran for two years. It led to ninety scientists being contacted and has, so far, led to six collections being deposited in the Wellcome Library, with additional collections being deposited in other UK repositories. In applying documentation strategy the HGAP was attempting to move away from traditional archival approaches to science, which have generally focused on retired Nobel Prize winners. It has been partially successful in this aim, having managed to secure collections from people who are not 'big names', but who made an important contribution to the HGP. However, the attempt to redress the gender imbalance in scientific collections and to improve record-keeping in scientific organisations has continued to be difficult to achieve. Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.

Similarities and differences in neuroplasticity mechanisms between brain gliomas and nonlesional epilepsy.

Science.gov (United States)

Bourdillon, Pierre; Apra, Caroline; Guénot, Marc; Duffau, Hugues

2017-12-01

To analyze the conceptual and practical implications of a hodotopic approach in neurosurgery, and to compare the similarities and the differences in neuroplasticity mechanisms between low-grade gliomas and nonlesional epilepsy. We review the recent data about the hodotopic organization of the brain connectome, alongside the organization of epileptic networks, and analyze how these two structures interact, suggesting therapeutic prospects. Then we focus on the mechanisms of neuroplasticity involved in glioma natural course and after glioma surgery. Comparing these mechanisms with those in action in an epileptic brain highlights their differences, but more importantly, gives an original perspective to the consequences of surgery on an epileptic brain and what could be expected after pathologic white matter removal. The organization of the brain connectome and the neuroplasticity is the same in all humans, but different pathologic mechanisms are involved, and specific therapeutic approaches have been developed in epilepsy and glioma surgery. We demonstrate that the "connectome" point of view can enrich epilepsy care. We also underscore how theoretical and practical tools commonly used in epilepsy investigations, such as invasive electroencephalography, can be of great help in awake surgery in general. Putting together advances in understanding of connectomics and neuroplasticity, leads to significant conceptual improvements in epilepsy surgery. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Interactional nursing--a practice-theory in the dynamic field between the natural, human and social sciences.

Science.gov (United States)

Scheel, Merry Elisabeth; Pedersen, Birthe D; Rosenkrands, Vibeke

2008-12-01

Nursing is often described from the point of view of either the natural or the human sciences. In contrast to this, the value foundation in Interactional nursing practice is understood from the point of view of the natural sciences as well as that of the human and social sciences. This article presents many-faceted practice-theory of nursing, which is situated in the dynamic field between these three sciences. The focus of the theory is on interaction and practice resulting in a caring practice. Here practice is based on Taylor's and MacIntyre's interpretation of this concept. Action in nursing is based on Habermas' three varied modes of action seen in the light of an understanding of the world as a system world and a life world. Nursing as an interactional practice-theory is presented with examples of interpretative nursing science, seen in the ethical action-oriented, socio-cultural framework of Taylor and Habermas. It is concluded that phenomenologic and socio-cultural research into caring practice as well as an in-depth, comprehensive interpretation of nursing practice are both highly suited to forming the fundamental theoretical framework in nursing, here seen as an interpretative nursing science. Finally, a comparison is drawn between Interactional nursing practice and Benner's theory of nursing practice.

MODELLING AND SIMULATING RISKS IN THE TRAINING OF THE HUMAN RESOURCES BY APPLYING THE CHAOS THEORY

OpenAIRE

Eugen ROTARESCU

2012-01-01

The article approaches the modelling and simulation of risks in the training of the human resources, as well as the forecast of the degree of human resources training impacted by risks by applying the mathematical tools offered by the Chaos Theory and mathematical statistics. We will highlight that the level of knowledge, skills and abilities of the human resources from an organization are autocorrelated in time and they depend on the level of a previous moment of the training, as well as on ...

Was Weber Wrong? A Human Capital Theory of Protestant Economic History. PEPG/07-04

Science.gov (United States)

Becker, Sascha O.; Wohmann, Ludger

2007-01-01

Max Weber attributed the higher economic prosperity of Protestant regions to a Protestant work ethic. We provide an alternative theory, where Protestant economies prospered because instruction in reading the Bible generated the human capital crucial to economic prosperity. County-level data from late 19th-century Prussia reveal that Protestantism…

Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI.

Science.gov (United States)

Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A

2018-01-01

Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks.

Biocultural Theory

DEFF Research Database (Denmark)

Carroll, Joseph; Clasen, Mathias; Jonsson, Emelie

2017-01-01

Biocultural theory is an integrative research program designed to investigate the causal interactions between biological adaptations and cultural constructions. From the biocultural perspective, cultural processes are rooted in the biological necessities of the human life cycle: specifically human...... of research as contributions to a coherent, collective research program. This article argues that a mature biocultural paradigm needs to be informed by at least 7 major research clusters: (a) gene-culture coevolution; (b) human life history theory; (c) evolutionary social psychology; (d) anthropological...... forms of birth, growth, survival, mating, parenting, and sociality. Conversely, from the biocultural perspective, human biological processes are constrained, organized, and developed by culture, which includes technology, culturally specific socioeconomic and political structures, religious...

Functional Connectome Analysis of Dopamine Neuron Glutamatergic Connections in Forebrain Regions.

Science.gov (United States)

Mingote, Susana; Chuhma, Nao; Kusnoor, Sheila V; Field, Bianca; Deutch, Ariel Y; Rayport, Stephen

2015-12-09

In the ventral tegmental area (VTA), a subpopulation of dopamine neurons express vesicular glutamate transporter 2 and make glutamatergic connections to nucleus accumbens (NAc) and olfactory tubercle (OT) neurons. However, their glutamatergic connections across the forebrain have not been explored systematically. To visualize dopamine neuron forebrain projections and to enable photostimulation of their axons independent of transmitter status, we virally transfected VTA neurons with channelrhodopsin-2 fused to enhanced yellow fluorescent protein (ChR2-EYFP) and used DAT(IREScre) mice to restrict expression to dopamine neurons. ChR2-EYFP-expressing neurons almost invariably stained for tyrosine hydroxylase, identifying them as dopaminergic. Dopamine neuron axons visualized by ChR2-EYFP fluorescence projected most densely to the striatum, moderately to the amygdala and entorhinal cortex (ERC), sparsely to prefrontal and cingulate cortices, and rarely to the hippocampus. Guided by ChR2-EYFP fluorescence, we recorded systematically from putative principal neurons in target areas and determined the incidence and strength of glutamatergic connections by activating all dopamine neuron terminals impinging on recorded neurons with wide-field photostimulation. This revealed strong glutamatergic connections in the NAc, OT, and ERC; moderate strength connections in the central amygdala; and weak connections in the cingulate cortex. No glutamatergic connections were found in the dorsal striatum, hippocampus, basolateral amygdala, or prefrontal cortex. These results indicate that VTA dopamine neurons elicit widespread, but regionally distinct, glutamatergic signals in the forebrain and begin to define the dopamine neuron excitatory functional connectome. Dopamine neurons are important for the control of motivated behavior and are involved in the pathophysiology of several major neuropsychiatric disorders. Recent studies have shown that some ventral midbrain dopamine neurons are

Small Worldness in Dense and Weighted Connectomes

Science.gov (United States)

Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas

2016-05-01

The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.

A Selected Review of the Underpinnings of Ethics for Human Performance Technology Professionals--Part One: Key Ethical Theories and Research.

Science.gov (United States)

Dean, Peter J.

1993-01-01

Provides a review of the key ethical theories and relevant empirical research relating to the practice of human performance technology. Topics addressed include ethics, morals, business ethics, ethics officers, empiricism versus normative ethical theory, consequentialism, utilitarianism, nonconsequentialism, Kohlberg model of cognitive moral…

Early-life experiences and the development of adult diseases with a focus on mental illness: The Human Birth Theory.

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Maccari, Stefania; Polese, Daniela; Reynaert, Marie-Line; Amici, Tiziana; Morley-Fletcher, Sara; Fagioli, Francesca

2017-02-07

In mammals, early adverse experiences, including mother-pup interactions, shape the response of an individual to chronic stress or to stress-related diseases during adult life. This has led to the elaboration of the theory of the developmental origins of health and disease, in particular adult diseases such as cardiovascular and metabolic disorders. In addition, in humans, as stated by Massimo Fagioli's Human Birth Theory, birth is healthy and equal for all individuals, so that mental illness develop exclusively in the postnatal period because of the quality of the relationship in the first year of life. Thus, this review focuses on the importance of programming during the early developmental period on the manifestation of adult diseases in both animal models and humans. Considering the obvious differences between animals and humans we cannot systematically move from animal models to humans. Consequently, in the first part of this review, we will discuss how animal models can be used to dissect the influence of adverse events occurring during the prenatal and postnatal periods on the developmental trajectories of the offspring, and in the second part, we will discuss the role of postnatal critical periods on the development of mental diseases in humans. Epigenetic mechanisms that cause reversible modifications in gene expression, driving the development of a pathological phenotype in response to a negative early postnatal environment, may lie at the core of this programming, thereby providing potential new therapeutic targets. The concept of the Human Birth Theory leads to a comprehension of the mental illness as a pathology of the human relationship immediately after birth and during the first year of life. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Social Learning Theory and Behavioral Therapy: Considering Human Behaviors within the Social and Cultural Context of Individuals and Families.

Science.gov (United States)

McCullough Chavis, Annie

2011-01-01

This article examines theoretical thoughts of social learning theory and behavioral therapy and their influences on human behavior within a social and cultural context. The article utilizes two case illustrations with applications for consumers. It points out the abundance of research studies concerning the effectiveness of social learning theory, and the paucity of research studies regarding effectiveness and evidence-based practices with diverse groups. Providing a social and cultural context in working with diverse groups with reference to social learning theory adds to the literature for more cultural considerations in adapting the theory to women, African Americans, and diverse groups.

Designing mental health interventions informed by child development and human biology theory: a social ecology intervention for child soldiers in Nepal.

Science.gov (United States)

Kohrt, Brandon A; Jordans, Mark J D; Koirala, Suraj; Worthman, Carol M

2015-01-01

The anthropological study of human biology, health, and child development provides a model with potential to address the gap in population-wide mental health interventions. Four key concepts from human biology can inform public mental health interventions: life history theory and tradeoffs, redundancy and plurality of pathways, cascades and multiplier effects in biological systems, and proximate feedback systems. A public mental health intervention for former child soldiers in Nepal is used to illustrate the role of these concepts in intervention design and evaluation. Future directions and recommendations for applying human biology theory in pursuit of public mental health interventions are discussed. © 2014 Wiley Periodicals, Inc.

Manual Labour, Intellectual Labour and Digital (Academic Labour. The Practice/Theory Debate in the Digital Humanities

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Christophe Magis

2018-01-01

Full Text Available Although it hasn’t much been considered as such, the Digital Humanities movements (or at least the most theoretically informed parts of it offers a critique “from within” of the recent mutation of the higher education and research systems. This paper offers an analysis, from a Critical Theory perspective, of a key element of this critique: the theory vs. practice debate, which, in the Digital Humanities, is translated into the famous “hack” versus “yack” motto, where DHers usually call for the pre-eminence of the former over the latter. I show how this debate aims to criticize the social situation of employment in academia in the digital age and can further be interpreted with the Cultural industry theoretical concept, as a continuance of the domination of the intellectual labour (ie. yack in this case over the manual labour (hack. Nevertheless, I argue that, pushing this debate to its very dialectical limit in the post-industrial academic labour situation, one realizes that the two terms aren’t in opposition anymore: the actual theory as well as the actual practice are below their very critical concepts in the academic labour. Therefore, I call for a reconfiguration of this debate, aiming at the rediscovering of an actual theory in the academic production, as well as a rediscovering of a praxis, the latter being outside of the scientific realm and rules: it is political.

Graph Theoretical Analysis Reveals: Women's Brains Are Better Connected than Men's.

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Balázs Szalkai

Full Text Available Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google's PageRank and the subsequent rise of the most popular search engine to date. Brain graphs, or connectomes, are being widely explored today. We believe that non-trivial graph theoretic concepts, similarly as it happened in the case of the World Wide Web, will lead to discoveries enlightening the structural and also the functional details of the animal and human brains. When scientists examine large networks of tens or hundreds of millions of vertices, only fast algorithms can be applied because of the size constraints. In the case of diffusion MRI-based structural human brain imaging, the effective vertex number of the connectomes, or brain graphs derived from the data is on the scale of several hundred today. That size facilitates applying strict mathematical graph algorithms even for some hard-to-compute (or NP-hard quantities like vertex cover or balanced minimum cut. In the present work we have examined brain graphs, computed from the data of the Human Connectome Project, recorded from male and female subjects between ages 22 and 35. Significant differences were found between the male and female structural brain graphs: we show that the average female connectome has more edges, is a better expander graph, has larger minimal bisection width, and has more spanning trees than the average male connectome. Since the average female brain weighs less than the brain of males, these properties show that the female brain has better graph theoretical properties, in a sense, than the brain of males. It is known that the female brain has a smaller gray matter/white matter ratio than males, that is, a larger white matter/gray matter ratio than the brain of males; this observation is in line with our findings concerning the number of edges, since the white matter consists of myelinated axons, which, in turn, roughly correspond to the connections

Evolutionary theory, human uniqueness and the image of God

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Gijsbert van den Brink

2012-10-01

Full Text Available In this article, I examined what might be called the evolutionary argument against human uniqueness and human dignity. After having rehearsed briefly the roots of the classical Judeo- Christian view on human uniqueness and human dignity in the first chapters of Genesis, I went on to explore and delineate the nature of the evolutionary argument against this view. Next, I examined whether Christian theology might widen the concept of imago Dei so as to include other beings as well as humans, thus giving up the idea of human uniqueness. I concluded, however, that this move is deeply problematic. Therefore, I turned to a discussion of some recent attempts to define both human uniqueness and the image of God in theological rather than empirical terms. One of these, which is based on the concept of incarnation, is found wanting, but another one is construed in such a way that it enables us to reconcile the idea of human uniqueness as encapsulated in the doctrine of the imago Dei with contemporary evolutionary theory. Thus, this article can be seen as an exercise in bringing classical Christian theology to terms with evolution, further highlighting this theology’s ongoing vitality. Evolusieteorie, menslike uniekheid and die beeld van God. In hierdie artikel ondersoek ek die sogenaamde evolusionêre argument teen menslike uniekheid en menswaardigheid. Na ‘n kort oorsig oor die oorsprong van die klassieke Joods-Christelike siening van menslike uniekheid en menswaardigheid soos uit die eerste vyf hoofstukke van Genesis blyk, ondersoek en beeld ek die aard van die evolusionêre argument hierteenoor uit. Vervolgens word die vraag ondersoek of die Christelike teologie die konsep van imago Dei sodanig kan verbreed dat dit ook ander wesens behalwe mense kan insluit, waardeur die idee van menslike uniekheid dus prysgegee word. Ek kom egter tot die slotsom dat hierdie skuif hoogs problematies is. Daarom wend ek my tot ’n bespreking van onlangse pogings om

Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI

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Nathan W. Churchill

Full Text Available Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70 university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1 a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings; and (2 a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks. Keywords: fMRI, Functional connectivity, Concussion, Brain injury, Symptoms

Creative Proactive-Concluding Theory of Motivating

OpenAIRE

Blašková, Martina

2010-01-01

The article deals with necessity to change the understanding of human resource philosophy to the new philosophy: philosophy of human potential. In these intentions, it is very important to motivate human potential in the organisations. But, in the area of motivating, situation within the organisations isn't sufficient. Thereto the article gives an introductive presentation of a new theory of motivating: creative proactive-concluding theory of motivating. The theory leads the managers to utili...

Putting a Realistic Theory of Mind into Agency Theory

DEFF Research Database (Denmark)

Foss, Nicolai Juul; Stea, Diego

2014-01-01

Agency theory is one of the most important foundational theories in management research, but it rests on contestable cognitive assumptions. Specifically, the principal is assumed to hold a perfect (correct) theory regarding some of the content of the agent's mind, while he is entirely ignorant...... concerning other such content. More realistically, individuals have some limited access to the minds of others. We explore the implications for classical agency theory of realistic assumptions regarding the human potential for interpersonal sensemaking. We discuss implications for the design and management...

Game theory.

Science.gov (United States)

Dufwenberg, Martin

2011-03-01

Game theory is a toolkit for examining situations where decision makers influence each other. I discuss the nature of game-theoretic analysis, the history of game theory, why game theory is useful for understanding human psychology, and why game theory has played a key role in the recent explosion of interest in the field of behavioral economics. WIREs Cogni Sci 2011 2 167-173 DOI: 10.1002/wcs.119 For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

The macro-structural variability of the human neocortex.

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Kruggel, Frithjof

2018-05-15

The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure. Copyright © 2018 Elsevier Inc. All rights reserved.

The Principal's Theory of Mind

DEFF Research Database (Denmark)

Foss, Nicolai Juul; Stea, Diego

Agency theory is one of the most important foundational theories in management research, but it rests on tenuous cognitive assumptions. We combine classical agency theory with a realistic theory of the intrinsically imperfect human potential for interpersonal sensemaking. This allows us...

Human Needs Theory: Applications for Music Education

Science.gov (United States)

Bates, Vincent C.

2009-01-01

In this article the author reviews needs theory as a field of research and scholarship, examines seven needs theories (including Nussbaum's capabilities approach), and synthesizes elements of all of these into a list he used tentatively and speculatively to analyze two common instructional practices in music education. The author's intent is to…

Quantifying the Role of Homophily in Human Cooperation Using Multiplex Evolutionary Game Theory.

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Alessandro Di Stefano

Full Text Available Nature shows as human beings live and grow inside social structures. This assumption allows us to explain and explore how it may shape most of our behaviours and choices, and why we are not just blindly driven by instincts: our decisions are based on more complex cognitive reasons, based on our connectedness on different spaces. Thus, human cooperation emerges from this complex nature of social network. Our paper, focusing on the evolutionary dynamics, is intended to explore how and why it happens, and what kind of impact is caused by homophily among people. We investigate the evolution of human cooperation using evolutionary game theory on multiplex. Multiplexity, as an extra dimension of analysis, allows us to unveil the hidden dynamics and observe non-trivial patterns within a population across network layers. More importantly, we find a striking role of homophily, as the higher the homophily between individuals, the quicker is the convergence towards cooperation in the social dilemma. The simulation results, conducted both macroscopically and microscopically across the network layers in the multiplex, show quantitatively the role of homophily in human cooperation.

CoCoMac 2.0 and the future of tract-tracing databases

OpenAIRE

Rembrandt eBakker; Rembrandt eBakker; Rembrandt eBakker; Thomas eWachtler; Markus eDiesmann; Markus eDiesmann; Markus eDiesmann

2012-01-01

The CoCoMac database contains the results of published axonal tract-tracing studies in the macaque brain. The combined data are used to construct the macaque macro-connectome. We discuss the redevelopment of CoCoMac and compare it to six connectome-related projects: two resources that provide online access to raw tracing data in rodents, a connectome viewer for advanced 3d graphics, a partial but highly detailed rat connectome, a brain data management system that generates custom connectivity...

["Grounded theory" develops medicine. Popular research method for exploring human behavior can discover new connections].

Science.gov (United States)

Thulesius, Hans; Barfod, Toke; Ekström, Helene; Håkansson, Anders

2004-09-30

Grounded theory (GT) is a popular research method for exploring human behavior. GT was developed by the medical sociologists Glaser and Strauss while they studied dying in hospitals in the 1960s resulting in the book "Awareness of dying". The goal of a GT is to generate conceptual theories by using all types of data but without applying existing theories and hypotheses. GT procedures are mostly inductive as opposed to deductive research where hypotheses are tested. A good GT has a core variable that is a central concept connected to many other concepts explaining the main action in the studied area. A core variable answers the question "What's going on?". Examples of core variables are: "Cutting back after a heart attack"--how people adapt to life after a serious illness; and "Balancing in palliative cancer care"--a process of weighing, shifting, compensating and compromising when treating people with a progressive and incurable illness trajectory.

Human-Agent Decision-making: Combining Theory and Practice

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Sarit Kraus

2016-06-01

Full Text Available Extensive work has been conducted both in game theory and logic to model strategic interaction. An important question is whether we can use these theories to design agents for interacting with people? On the one hand, they provide a formal design specification for agent strategies. On the other hand, people do not necessarily adhere to playing in accordance with these strategies, and their behavior is affected by a multitude of social and psychological factors. In this paper we will consider the question of whether strategies implied by theories of strategic behavior can be used by automated agents that interact proficiently with people. We will focus on automated agents that we built that need to interact with people in two negotiation settings: bargaining and deliberation. For bargaining we will study game-theory based equilibrium agents and for argumentation we will discuss logic-based argumentation theory. We will also consider security games and persuasion games and will discuss the benefits of using equilibrium based agents.

A network engineering perspective on probing and perturbing cognition with neurofeedback.

Science.gov (United States)

Bassett, Danielle S; Khambhati, Ankit N

2017-05-01

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

Plans, Habits, and Theory of Mind.

Science.gov (United States)

Gershman, Samuel J; Gerstenberg, Tobias; Baker, Chris L; Cushman, Fiery A

2016-01-01

Human success and even survival depends on our ability to predict what others will do by guessing what they are thinking. If I accelerate, will he yield? If I propose, will she accept? If I confess, will they forgive? Psychologists call this capacity "theory of mind." According to current theories, we solve this problem by assuming that others are rational actors. That is, we assume that others design and execute efficient plans to achieve their goals, given their knowledge. But if this view is correct, then our theory of mind is startlingly incomplete. Human action is not always a product of rational planning, and we would be mistaken to always interpret others' behaviors as such. A wealth of evidence indicates that we often act habitually-a form of behavioral control that depends not on rational planning, but rather on a history of reinforcement. We aim to test whether the human theory of mind includes a theory of habitual action and to assess when and how it is deployed. In a series of studies, we show that human theory of mind is sensitive to factors influencing the balance between habitual and planned behavior.

Disrupted Module Efficiency of Structural and Functional Brain Connectomes in Clinically Isolated Syndrome and Multiple Sclerosis

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Yaou Liu

2018-04-01

Full Text Available Recent studies have demonstrated disrupted topological organization of brain connectome in multiple sclerosis (MS. However, whether the communication efficiency between different functional systems is affected in the early stage of MS remained largely unknown. In this study, we constructed the structural connectivity (SC and functional connectivity (FC networks in 41 patients with clinically isolated syndrome (CIS, 32 MS patients and 35 healthy controls (HC based on diffusion and resting-state functional MRI. To quantify the communication efficiency within and between different functional systems, we proposed two measures called intra- and inter-module efficiency. Based on the module parcellation of functional backbone network, the intra- and inter-module efficiency of SC and FC networks was calculated for each participant. For the SC network, CIS showed decreased inter-module efficiency between the sensory-motor network (SMN, the visual network (VN, the default-mode network (DMN and the fronto-parietal network (FPN compared with HC, while MS showed more widespread decreased module efficiency both within and between modules relative to HC and CIS. For the FC network, no differences were found between CIS and HC, and a decreased inter-module efficiency between SMN and FPN and between VN and FPN was identified in MS, compared with HC and CIS. Moreover, both intra- and inter-module efficiency of SC network were correlated with the disability and cognitive scores in MS. Therefore, our results demonstrated early SC changes between modules in CIS, and more widespread SC alterations and inter-module FC changes were observed in MS, which were further associated with cognitive impairment and physical disability.

Exploring the Associations Between Intrinsic Brain Connectivity and Creative Ability Using Functional Connectivity Strength and Connectome Analysis.

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Gao, Zhenni; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Cai, Yuxuan; Li, Junchao; Gao, Mengxia; Liu, Xiaojin; Chang, Song; Jiao, Bingqing; Huang, Ruiwang; Liu, Ming

2017-11-01

The present study aimed to explore the association between resting-state functional connectivity and creativity ability. Toward this end, the figural Torrance Tests of Creative Thinking (TTCT) scores were collected from 180 participants. Based on the figural TTCT measures, we collected resting-state functional magnetic resonance imaging data for participants with two different levels of creativity ability (a high-creativity group [HG, n = 22] and a low-creativity group [LG, n = 20]). For the aspect of group difference, this study combined voxel-wise functional connectivity strength (FCS) and seed-based functional connectivity to identify brain regions with group-change functional connectivity. Furthermore, the connectome properties of the identified regions and their associations with creativity were investigated using the permutation test, discriminative analysis, and brain-behavior correlation analysis. The results indicated that there were 4 regions with group differences in FCS, and these regions were linked to 30 other regions, demonstrating different functional connectivity between the groups. Together, these regions form a creativity-related network, and we observed higher network efficiency in the HG compared with the LG. The regions involved in the creativity network were widely distributed across the modality-specific/supramodality cerebral cortex, subcortex, and cerebellum. Notably, properties of regions in the supramodality networks (i.e., the default mode network and attention network) carried creativity-level discriminative information and were significantly correlated with the creativity performance. Together, these findings demonstrate a link between intrinsic brain connectivity and creative ability, which should provide new insights into the neural basis of creativity.

Image quality transfer and applications in diffusion MRI

DEFF Research Database (Denmark)

Alexander, Daniel C.; Zikic, Darko; Ghosh, Aurobrata

2017-01-01

and the uniquely rich diffusion MRI data set from the human connectome project (HCP). Results highlight potential benefits of IQT in both brain connectivity mapping and microstructure imaging. In brain connectivity mapping, IQT reveals, from standard data sets, thin connection pathways that tractography normally...

Psychological Defenses against Death Anxiety: Integrating Terror Management Theory and Firestone's Separation Theory

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Bassett, Jonathan F.

2007-01-01

The author attempts to integrate Terror Management Theory (TMT) and R. W. Firestone's Separation Theory (1984, 1994). Both theories emphasize defense against death anxiety as a key human motive. Whereas TMT focuses extensively on self-esteem and cultural worldview, Firestone posited additional defenses such as gene survival, self-nourishing…

Essays in auction theory

NARCIS (Netherlands)

Maasland, E.

2012-01-01

Auction theory is a branch of game theory that considers human behavior in auction markets and the ensuing market outcomes. It is also successfully used as a tool to design real-life auctions. This thesis contains five essays addressing a variety of topics within the realm of auction theory. The

Progress in Application of the Neurosciences to an Understanding of Human Learning: The Challenge of Finding a Middle-Ground Neuroeducational Theory

Science.gov (United States)

Anderson, O. Roger

2014-01-01

Modern neuroscientific research has substantially enhanced our understanding of the human brain. However, many challenges remain in developing a strong, brain-based theory of human learning, especially in complex environments such as educational settings. Some of the current issues and challenges in our progress toward developing comprehensive…

Critical Theory of Human Rights

NARCIS (Netherlands)

Rensmann, Lars; Thompson, Michael J.

2017-01-01

International human rights have become an important global norm that has increasingly been incorporated into international law and global conventions. Human rights are a key reference point of mobilizations by diverse groups and international nongovernmental organization (INGOs) in global publics

Comprehensive in vivo mapping of the human basal ganglia and thalamic connectome in individuals using 7T MRI.

Directory of Open Access Journals (Sweden)

Christophe Lenglet

Full Text Available Basal ganglia circuits are affected in neurological disorders such as Parkinson's disease (PD, essential tremor, dystonia and Tourette syndrome. Understanding the structural and functional connectivity of these circuits is critical for elucidating the mechanisms of the movement and neuropsychiatric disorders, and is vital for developing new therapeutic strategies such as deep brain stimulation (DBS. Knowledge about the connectivity of the human basal ganglia and thalamus has rapidly evolved over recent years through non-invasive imaging techniques, but has remained incomplete because of insufficient resolution and sensitivity of these techniques. Here, we present an imaging and computational protocol designed to generate a comprehensive in vivo and subject-specific, three-dimensional model of the structure and connections of the human basal ganglia. High-resolution structural and functional magnetic resonance images were acquired with a 7-Tesla magnet. Capitalizing on the enhanced signal-to-noise ratio (SNR and enriched contrast obtained at high-field MRI, detailed structural and connectivity representations of the human basal ganglia and thalamus were achieved. This unique combination of multiple imaging modalities enabled the in-vivo visualization of the individual human basal ganglia and thalamic nuclei, the reconstruction of seven white-matter pathways and their connectivity probability that, to date, have only been reported in animal studies, histologically, or group-averaged MRI population studies. Also described are subject-specific parcellations of the basal ganglia and thalamus into sub-territories based on their distinct connectivity patterns. These anatomical connectivity findings are supported by functional connectivity data derived from resting-state functional MRI (R-fMRI. This work demonstrates new capabilities for studying basal ganglia circuitry, and opens new avenues of investigation into the movement and neuropsychiatric

A theory of unconscious thought

NARCIS (Netherlands)

Dijksterhuis, A.J.; Nordgren, L.F.

2006-01-01

We present a theory about human thought named the unconscious-thought theory (UTT). The theory is applicable to decision making, impression formation, attitude formation and change, problem solving, and creativity. It distinguishes between two modes of thought: unconscious and conscious. Unconscious

An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks

NARCIS (Netherlands)

G.W.C. Paas (Fred); J. Sweller (John)

2012-01-01

textabstractCognitive load theory is intended to provide instructional strategies derived from experimental, cognitive load effects. Each effect is based on our knowledge of human cognitive architecture, primarily the limited capacity and duration of a human working memory. These limitations are

Activity theory as a challenge to systems design

DEFF Research Database (Denmark)

Bødker, Susanne

1991-01-01

This paper suggests an improvement of the theoretical foundation of information systems research of the 1990s. This foundation is found in human activity theory. The paper deals with how human activity theory can help systems design change, theoretically and practically. Applying activity theory...

Some Sociological Alternatives to Human Capital Theory and Their Implications for Research on Post-Compulsory Education and Training.

Science.gov (United States)

Fevre, Ralph; Rees, Gareth; Gorard, Stephen

1999-01-01

Based on research in South Wales, a sociological theory of participation in education and training is developed, identifying types of orientations: functional avoidance, instrumental credentialism, and vocational transformation. The inclusion of sociological insights in human-capital development policy is recommended. (SK)

A Random Riemannian Metric for Probabilistic Shortest-Path Tractography

DEFF Research Database (Denmark)

Hauberg, Søren; Schober, Michael; Liptrot, Matthew George

2015-01-01

of the diffusion tensor as a “random Riemannian metric”, where a geodesic is a distribution over tracts. We approximate this distribution with a Gaussian process and present a probabilistic numerics algorithm for computing the geodesic distribution. We demonstrate SPT improvements on data from the Human Connectome...

Non-cooperative game theory in biology and cooperative reasoning in humans.

Science.gov (United States)

Kabalak, Alihan; Smirnova, Elena; Jost, Jürgen

2015-06-01

The readiness for spontaneous cooperation together with the assumptions that others share this cooperativity has been identified as a fundamental feature that distinguishes humans from other animals, including the great apes. At the same time, cooperativity presents an evolutionary puzzle because non-cooperators do better in a group of cooperators. We develop here an analysis of the process leading to cooperation in terms of rationality concepts, game theory and epistemic logic. We are, however, not attempting to reconstruct the actual evolutionary process. We rather want to provide the logical structure underlying cooperation in order to understand why cooperation is possible and what kind of reasoning and beliefs would lead to cooperative decision-making. Game theory depends on an underlying common belief in non-cooperative rationality of the players, and cooperativity similarly can utilize a common belief in cooperative rationality as its basis. We suggest a weaker concept of rational decision-making in games that encompasses both types of decision-making. We build this up in stages, starting from simple optimization, then using anticipation of the reaction of others, to finally arrive at reflexive and cooperative reasoning. While each stage is more difficult than the preceding, importantly, we also identify a reduction of complexity achieved by the consistent application of higher stage reasoning.

Editorial of the Special Issue on Human-Technology Interaction and Technology Adoption: Exploring Frameworks other than Actor-Network Theory

DEFF Research Database (Denmark)

Tanev, Stoyan

2014-01-01

Actor-network theory (ANT) has established itself as a valuable resource for the analysis of technology innovation and adoption. One of the main reasons for the success of the Innovation Translation Model (a specific instantiation of ANT) is the fact that it fits very well the emerging dominance...... challenges. This is why in this special issue we have focused on exploring, in parallel to ANT, other approaches that have also proven valuable in studying technology adoption and human-technology interaction. Some of these approaches share significant common ground with ANT. They also diverge in some......, Design in-use, Practice theory, Innovation diffusion, Consumer innovativeness and Activity theory....

What genre theory does

DEFF Research Database (Denmark)

Andersen, Jack

2015-01-01

Purpose To provide a small overview of genre theory and its associated concepts and to show how genre theory has had its antecedents in certain parts of the social sciences and not in the humanities. Findings The chapter argues that the explanatory force of genre theory may be explained with its...... emphasis on everyday genres, de facto genres. Originality/value By providing an overview of genre theory, the chapter demonstrates the wealth and richness of forms of explanations in genre theory....

Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome.

Science.gov (United States)

Batalle, Dafnis; Eixarch, Elisenda; Figueras, Francesc; Muñoz-Moreno, Emma; Bargallo, Nuria; Illa, Miriam; Acosta-Rojas, Ruthy; Amat-Roldan, Ivan; Gratacos, Eduard

2012-04-02

Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the

The CONNECT project: Combining macro- and micro-structure.

Science.gov (United States)

Assaf, Yaniv; Alexander, Daniel C; Jones, Derek K; Bizzi, Albero; Behrens, Tim E J; Clark, Chris A; Cohen, Yoram; Dyrby, Tim B; Huppi, Petra S; Knoesche, Thomas R; Lebihan, Denis; Parker, Geoff J M; Poupon, Cyril; Anaby, Debbie; Anwander, Alfred; Bar, Leah; Barazany, Daniel; Blumenfeld-Katzir, Tamar; De-Santis, Silvia; Duclap, Delphine; Figini, Matteo; Fischi, Elda; Guevara, Pamela; Hubbard, Penny; Hofstetter, Shir; Jbabdi, Saad; Kunz, Nicolas; Lazeyras, Francois; Lebois, Alice; Liptrot, Matthew G; Lundell, Henrik; Mangin, Jean-François; Dominguez, David Moreno; Morozov, Darya; Schreiber, Jan; Seunarine, Kiran; Nava, Simone; Poupon, Cyril; Riffert, Till; Sasson, Efrat; Schmitt, Benoit; Shemesh, Noam; Sotiropoulos, Stam N; Tavor, Ido; Zhang, Hui Gary; Zhou, Feng-Lei

2013-10-15

In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractography to infer connectivity between brain regions. In parallel to the development of tractography, additional diffusion MRI based frameworks (CHARMED, AxCaliber, ActiveAx) were developed enabling the extraction of a multitude of micro-structural parameters (axon diameter distribution, mean axonal diameter and axonal density). This unique insight into both tissue microstructure and connectivity has enormous potential value in understanding the structure and organization of the brain as well as providing unique insights to abnormalities that underpin disease states. The CONNECT (Consortium Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper summarizes the project and describes the perspective of using micro-structural measures to study the connectome. Copyright © 2013 Elsevier Inc. All rights reserved.

Culture Studies and Self-Actualization Theory.

Science.gov (United States)

Farmer, Rod

1983-01-01

True citizenship education is impossible unless students develop the habit of intelligently evaluating cultures. Abraham Maslow's theory of self-actualization, a theory of innate human needs and of human motivation, is a nonethnocentric tool which can be used by teachers and students to help them understand other cultures. (SR)

Predicting human papillomavirus vaccine uptake in young adult women: Comparing the Health Belief Model and Theory of Planned Behavior

Science.gov (United States)

Gerend, Mary A.; Shepherd, Janet E.

2012-01-01

Background Although theories of health behavior have guided thousands of studies, relatively few studies have compared these theories against one another. Purpose The purpose of the current study was to compare two classic theories of health behavior—the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB)—in their prediction of human papillomavirus (HPV) vaccination. Methods After watching a gain-framed, loss-framed, or control video, women (N=739) ages 18–26 completed a survey assessing HBM and TPB constructs. HPV vaccine uptake was assessed ten months later. Results Although the message framing intervention had no effect on vaccine uptake, support was observed for both the TPB and HBM. Nevertheless, the TPB consistently outperformed the HBM. Key predictors of uptake included subjective norms, self-efficacy, and vaccine cost. Conclusions Despite the observed advantage of the TPB, findings revealed considerable overlap between the two theories and highlighted the importance of proximal versus distal predictors of health behavior. PMID:22547155

Toward a theory of holistic needs and the brain.

Science.gov (United States)

Silton, Nava R; Flannelly, Laura T; Flannelly, Kevin J; Galek, Kathleen

2011-01-01

This article reviews Maslow's theory of motivation wherein he proposes a hierarchy of human needs. First, it describes the principal elements of Maslow's theory and discusses considerations relating to the flexibility of the hierarchy. Second, it explains the relationship among Maslow's theory of human needs, attachment theory, and evolutionary threat assessment system theory. Third, it provides an overview of the brain structures posited to be involved in attachment and evolutionary threat assessment system theory and their relation to Maslow's hierarchy. Finally, it explains how the 3 theories converge to form a theory of holistic needs.

Risk communication: Framing versus interdependence theory

International Nuclear Information System (INIS)

Lawless, W.F.; Burns, Chad W.

1992-01-01

Prospect theory has gained wide acceptance since its introduction by Kahneman and Tversky, especially where it has been applied extensively by DOE and others. But as conceived, it is a static process theory that may not apply to dynamic environments or dynamic processes; indeed, the recent extension to group situations by one of its authors modified the original conclusions. Although most social science research is static in nature, if prospect theory is to apply to human behavior, as the authors do with their sweeping generalizations about human irrationality, because behavior is dynamic and not static, then the challenge is to study prospect theory in a dynamic environment. This study will briefly review prospect and interdependence theories, representative evidence that distinguishes between the two theories, and the implications for DOE nuclear waste management. (author)

Cross-population myelination covariance of human cerebral cortex.

Science.gov (United States)

Ma, Zhiwei; Zhang, Nanyin

2017-09-01

Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small-worldness. Furthermore, we found that the correlation between myelination covariance and resting-state functional connectivity (RSFC) was uniform within each resting-state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance-RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730-4743, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The neonatal brain : early connectome development and childhood cognition

NARCIS (Netherlands)

Keunen, K.

2017-01-01

The human brain is a vastly complex system that develops rapidly during human gestation. Its developmental pace is unprecedented in any other period of human development. By the time of normal birth the brain's layout verges on the adult human brain. All major structures have come into place,

Dynamic Network Communication in the Human Functional Connectome Predicts Perceptual Variability in Visual Illusion.

Science.gov (United States)

Wang, Zhiwei; Zeljic, Kristina; Jiang, Qinying; Gu, Yong; Wang, Wei; Wang, Zheng

2018-01-01

Ubiquitous variability between individuals in visual perception is difficult to standardize and has thus essentially been ignored. Here we construct a quantitative psychophysical measure of illusory rotary motion based on the Pinna-Brelstaff figure (PBF) in 73 healthy volunteers and investigate the neural circuit mechanisms underlying perceptual variation using functional magnetic resonance imaging (fMRI). We acquired fMRI data from a subset of 42 subjects during spontaneous and 3 stimulus conditions: expanding PBF, expanding modified-PBF (illusion-free) and expanding modified-PBF with physical rotation. Brain-wide graph analysis of stimulus-evoked functional connectivity patterns yielded a functionally segregated architecture containing 3 discrete hierarchical networks, commonly shared between rest and stimulation conditions. Strikingly, communication efficiency and strength between 2 networks predominantly located in visual areas robustly predicted individual perceptual differences solely in the illusory stimulus condition. These unprecedented findings demonstrate that stimulus-dependent, not spontaneous, dynamic functional integration between distributed brain networks contributes to perceptual variability in humans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Tried and true: self-regulation theory as a guiding framework for teaching parents diabetes education using human patient simulation.

Science.gov (United States)

Sullivan-Bolyai, Susan; Johnson, Kimberly; Cullen, Karen; Hamm, Terry; Bisordi, Jean; Blaney, Kathleen; Maguire, Laura; Melkus, Gail

2014-01-01

Parents become emotionally upset when learning that their child has type 1 diabetes, yet they are expected to quickly learn functional diabetes management. The purpose of this article is to describe the application of self-regulation theory to guide a family-focused education intervention using human patient simulation to enhance the initial education of parents in diabetes management. A brief description is provided of the intervention framed by self-regulation theory. On the basis of the literature, we describe the educational vignettes used based on self-regulation in the randomized controlled trial entitled "Parent Education Through Simulation-Diabetes." Examples of theory-in-practice will be illustrated by parental learning responses to this alternative educational innovation.

Education, poverty and the 'missing link': The limits of human capital theory as a paradigm for poverty reduction

NARCIS (Netherlands)

Bonal, X.; Mundy, K.; Green, A.; Lingard, R.; Verger, A.

2016-01-01

One of the main areas where human capital theory has been especially influential is in the relationship between investment in education and poverty reduction. However, up to now, little success can be reported, with huge differences between the average levels of education globally achieved and the

Sex differences, evolutionary psychology and biosocial theory : Biosocial theory is no alternative

NARCIS (Netherlands)

Luxen, Marc F.

Biosocial theory claims that evolution did not design human psychological sex differences. It argues that these are the result of the allocation of men and women into different sex roles, based on physical differences. This article argues, however, that biosocial theory is not an alternative to

An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks

Science.gov (United States)

Paas, Fred; Sweller, John

2012-01-01

Cognitive load theory is intended to provide instructional strategies derived from experimental, cognitive load effects. Each effect is based on our knowledge of human cognitive architecture, primarily the limited capacity and duration of a human working memory. These limitations are ameliorated by changes in long-term memory associated with…

Nursing intellectual capital theory: testing selected propositions.

Science.gov (United States)

Covell, Christine L; Sidani, Souraya

2013-11-01

To test the selected propositions of the middle-range theory of nursing intellectual capital. The nursing intellectual capital theory conceptualizes nursing knowledge's influence on patient and organizational outcomes. The theory proposes nursing human capital, nurses' knowledge, skills and experience, is related to the quality of patient care and nurse recruitment and retention of an inpatient care unit. Two factors in the work environment, nurse staffing and employer support for nurse continuing professional development, are proposed to influence nursing human capital's association with patient and organizational outcomes. A cross-sectional survey design. The study took place in 2008 in six Canadian acute care hospitals. Financial, human resource and risk data were collected from hospital departments and unit managers. Clearly specified empirical indicators quantified the study variables. The propositions of the theory were tested with data from 91 inpatient care units using structural equation modelling. The propositions associated with the nursing human capital concept were supported. The propositions associated with the employer support for nurse continuing professional development concept were not. The proposition that nurse staffing's influences on patient outcomes was mediated by the nursing human capital of an inpatient unit, was partially supported. Some of the theory's propositions were empirically validated. Additional theoretical work is needed to refine the operationalization and measurement of some of the theory's concepts. Further research with larger samples of data from different geographical settings and types of hospitals is required to determine if the theory can withstand empirical scrutiny. © 2013 Blackwell Publishing Ltd.

Novel theory of the human brain: information-commutation basis of architecture and principles of operation

Directory of Open Access Journals (Sweden)

Bryukhovetskiy AS

2015-02-01

Full Text Available Andrey S Bryukhovetskiy Center for Biomedical Technologies, Federal Research and Clinical Center for Specialized Types of Medical Assistance and Medical Technologies of the Federal Medical Biological Agency, NeuroVita Clinic of Interventional and Restorative Neurology and Therapy, Moscow, Russia Abstract: Based on the methodology of the informational approach and research of the genome, proteome, and complete transcriptome profiles of different cells in the nervous tissue of the human brain, the author proposes a new theory of information-commutation organization and architecture of the human brain which is an alternative to the conventional systemic connective morphofunctional paradigm of the brain framework. Informational principles of brain operation are defined: the modular principle, holographic principle, principle of systematicity of vertical commutative connection and complexity of horizontal commutative connection, regulatory principle, relay principle, modulation principle, “illumination” principle, principle of personalized memory and intellect, and principle of low energy consumption. The author demonstrates that the cortex functions only as a switchboard and router of information, while information is processed outside the nervous tissue of the brain in the intermeningeal space. The main structural element of information-commutation in the brain is not the neuron, but information-commutation modules that are subdivided into receiver modules, transmitter modules, and subscriber modules, forming a vertical architecture of nervous tissue in the brain as information lines and information channels, and a horizontal architecture as central, intermediate, and peripheral information-commutation platforms. Information in information-commutation modules is transferred by means of the carriers that are characteristic to the specific information level from inductome to genome, transcriptome, proteome, metabolome, secretome, and magnetome

Eight myths on motivating social services workers: theory-based perspectives.

Science.gov (United States)

Latting, J K

1991-01-01

A combination of factors has made formal motivational and reward systems rare in human service organizations generally and virtually non-existent in social service agencies. The author reviews eight of these myths by reference to eight motivational theories which refute them: need theory, expectancy theory, feedback theory, equity theory, reinforcement theory, cognitive evaluation theory, goal setting theory, and social influence theory. Although most of these theories have been developed and applied in the private sector, relevant research has also been conducted in social service agencies. The author concludes with a summary of guidelines suggested by the eight theories for motivating human service workers.

Trends in Opportunity Costs of U.S. Postsecondary Education: A National HRD and Human Capital Theory Analysis

Science.gov (United States)

Cornacchione, Edgard; Daugherty, Jenny L.

2013-01-01

The purpose of this study was to explore opportunity costs of postsecondary education in the U.S. in the past three decades (1975-2005), as a measure to support investment decisions at national levels and as experienced by individuals deciding on pursuing further education. Based on human capital theory and inspired by a set of studies aiming at…

Documentary and Cognitive Theory

DEFF Research Database (Denmark)

Bondebjerg, Ib

2014-01-01

This article deals with the benefits of using cognitive theory in documentary film studies. The article outlines general aspects of cognitive theory in humanities and social science, however the main focus is on the role of narrative, visual style and emotional dimensions of different types...

Human disease mortality kinetics are explored through a chain model embodying principles of extreme value theory and competing risks.

Science.gov (United States)

Juckett, D A; Rosenberg, B

1992-04-21

The distributions for human disease-specific mortality exhibit two striking characteristics: survivorship curves that intersect near the longevity limit; and, the clustering of best-fitting Weibull shape parameter values into groups centered on integers. Correspondingly, we have hypothesized that the distribution intersections result from either competitive processes or population partitioning and the integral clustering in the shape parameter results from the occurrence of a small number of rare, rate-limiting events in disease progression. In this report we initiate a theoretical examination of these questions by exploring serial chain model dynamics and parameteric competing risks theory. The links in our chain models are composed of more than one bond, where the number of bonds in a link are denoted the link size and are the number of events necessary to break the link and, hence, the chain. We explored chains with all links of the same size or with segments of the chain composed of different size links (competition). Simulations showed that chain breakage dynamics depended on the weakest-link principle and followed kinetics of extreme-values which were very similar to human mortality kinetics. In particular, failure distributions for simple chains were Weibull-type extreme-value distributions with shape parameter values that were identifiable with the integral link size in the limit of infinite chain length. Furthermore, for chains composed of several segments of differing link size, the survival distributions for the various segments converged at a point in the S(t) tails indistinguishable from human data. This was also predicted by parameteric competing risks theory using Weibull underlying distributions. In both the competitive chain simulations and the parametric competing risks theory, however, the shape values for the intersecting distributions deviated from the integer values typical of human data. We conclude that rare events can be the source of

Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer.

Science.gov (United States)

Kesler, Shelli R; Watson, Christa L; Blayney, Douglas W

2015-08-01

Breast cancer and its treatments are associated with mild cognitive impairment and brain changes that could indicate an altered or accelerated brain aging process. We applied diffusion tensor imaging and graph theory to measure white matter organization and connectivity in 34 breast cancer survivors compared with 36 matched healthy female controls. We also investigated how brain networks (connectomes) in each group responded to simulated neurodegeneration based on network attack analysis. Compared with controls, the breast cancer group demonstrated significantly lower fractional anisotropy, altered small-world connectome properties, lower brain network tolerance to systematic region (node), and connection (edge) attacks and significant cognitive impairment. Lower tolerance to network attack was associated with cognitive impairment in the breast cancer group. These findings provide further evidence of diffuse white matter pathology after breast cancer and extend the literature in this area with unique data demonstrating increased vulnerability of the post-breast cancer brain network to future neurodegenerative processes. Copyright © 2015 Elsevier Inc. All rights reserved.

Information Foraging Theory: A Framework for Intelligence Analysis

Science.gov (United States)

2014-11-01

oceanographic information, human intelligence (HUMINT), open-source intelligence ( OSINT ), and information provided by other governmental departments [1][5...Human Intelligence IFT Information Foraging Theory LSA Latent Semantic Similarity MVT Marginal Value Theorem OFT Optimal Foraging Theory OSINT

Social Learning, Social Control, and Strain Theories: A Formalization of Micro-level Criminological Theories

OpenAIRE

Proctor, Kristopher Ryan

2010-01-01

This dissertation proposes theoretical formalization as a way of enhancing theory development within criminology. Differential association, social learning, social control, and general strain theories are formalized in order to identify assumptions of human nature, key theoretical concepts, theoretical knowledge claims, and scope conditions. The resulting formalization allows greater comparability between theories in terms of explanatory power, and additionally provides insights into integrat...

Think Human

DEFF Research Database (Denmark)

Nielsen, Charlotte Marie Bisgaard

2013-01-01

years' campaigns suggests that the theory of communication underlying the campaign has its basis in mechanical action rather than in human communication. The practice of 'Communication design' is investigated in relation to this metaphorical 'machine thinking' model of communication and contrasted...... with the human-centered theory of communication advocated by integrationism....

A decision support system prototype including human factors based on the TOGA meta-theory approach

International Nuclear Information System (INIS)

Cappelli, M.; Memmi, F.; Gadomski, A. M.; Sepielli, M.

2012-01-01

The human contribution to the risk of operation of complex technological systems is often not negligible and sometimes tends to become significant, as shown by many reports on incidents and accidents occurred in the past inside Nuclear Power Plants (NPPs). An error of a human operator of a NPP can derive by both omission and commission. For instance, complex commission errors can also lead to significant catastrophic technological accidents, as for the case of the Three Mile Island accident. Typically, the problem is analyzed by focusing on the single event chain that has provoked the incident or accident. What is needed is a general framework able to include as many parameters as possible, i.e. both technological and human factors. Such a general model could allow to envisage an omission or commission error before it can happen or, alternatively, suggest preferred actions to do in order to take countermeasures to neutralize the effect of the error before it becomes critical. In this paper, a preliminary Decision Support System (DSS) based on the so-called (-) TOGA meta-theory approach is presented. The application of such a theory to the management of nuclear power plants has been presented in the previous ICAPP 2011. Here, a human factor simulator prototype is proposed in order to include the effect of human errors in the decision path. The DSS has been developed using a TRIGA research reactor as reference plant, and implemented using the LabVIEW programming environment and the Finite State Machine (FSM) model The proposed DSS shows how to apply the Universal Reasoning Paradigm (URP) and the Universal Management Paradigm (UMP) to a real plant context. The DSS receives inputs from instrumentation data and gives as output a suggested decision. It is obtained as the result of an internal elaborating process based on a performance function. The latter, describes the degree of satisfaction and efficiency, which are dependent on the level of responsibility related to

Extracting Intrinsic Functional Networks with Feature-Based Group Independent Component Analysis

Science.gov (United States)

Calhoun, Vince D.; Allen, Elena

2013-01-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in…

Falsification of matching theory and confirmation of an evolutionary theory of behavior dynamics in a critical experiment.

Science.gov (United States)

McDowell, J J; Calvin, Olivia L; Hackett, Ryan; Klapes, Bryan

2017-07-01

Two competing predictions of matching theory and an evolutionary theory of behavior dynamics, and one additional prediction of the evolutionary theory, were tested in a critical experiment in which human participants worked on concurrent schedules for money (Dallery et al., 2005). The three predictions concerned the descriptive adequacy of matching theory equations, and of equations describing emergent equilibria of the evolutionary theory. Tests of the predictions falsified matching theory and supported the evolutionary theory. Copyright © 2017 Elsevier B.V. All rights reserved.

MOTIVATING ENGLISH TEACHERS BASED ON THE BASIC NEEDS THEORY AND AN EXPECTANCY THEORY

Directory of Open Access Journals (Sweden)

Hidayatus Sholihah

2017-08-01

Full Text Available There are two main motivation theories. a hierarchy of basic needs theory,  and an expectancy theory. In a Hyrarchy of basic needs theory, Maslow has stated that the basic needs as a main behaviour direction are structured into a hierarchy. There are five basic human needs.  The first: Physiological needs such as: salary, bonus or working condition. The second: the safety needs, such as: safe job environment, job security or health cover. The third, social needs, such as  union and team work. The next is self esteem, such as getting an award, medal, certificate or any other recognisition. Then the last is self actualization, for example is by providing an opportunity to share knowledge, skills and eprerience. The evaluation of this theory are: there is no spiritual needs as human basic needs is a main weakness of this theory. Then it is possible that different level of  needs  have to be satisfied in the same time, or not in hierarchy level or, not always have to be fulfilled in order. The next motivation theory is an Expectancy Theory. This theory is based on three main factors. The first factor is: English teachers will be motivated to work harder if they have a good perception to their own competences in accordance with their job. The second, individual motivation depends on the rewards given when they finish a  particular job. Finally, it also depends on their regards to the rewards given from the job that they do. Expectancy theory is a good theory, however, it is not easy to be implemented because the principals should provide various types of reward to satisfy the expectation of their English teachers. Considering the strengths and weaknesses of these two theories, it is better to combine both of them in the practice to get more effective results.

Theory Analysis and Experiment Research of the Leg Mechanism for the Human-Carrying Walking Chair Robot

Directory of Open Access Journals (Sweden)

Lingfeng Sang

2014-01-01

Full Text Available For the high carrying capacity of the human-carrying walking chair robot, in this paper, 2-UPS+UP parallel mechanism is selected as the leg mechanism; then kinematics, workspace, control, and experiment of the leg mechanism are researched in detail. Firstly, design of the whole mechanism is described and degrees of freedom of the leg mechanism are analyzed. Second, the forward position, inverse position, and velocity of leg mechanism are studied. Third, based on the kinematics analysis and the structural constraints, the reachable workspace of 2-UPS+UP parallel mechanism is solved, and then the optimal motion workspace is searched in the reachable workspace by choosing the condition number as the evaluation index. Fourth, according to the theory analysis of the parallel leg mechanism, its control system is designed and the compound position control strategy is studied. Finally, in optimal motion workspace, the compound position control strategy is verified by using circular track with the radius 100 mm; the experiment results show that the leg mechanism moves smoothly and does not tremble obviously. Theory analysis and experiment research of the single leg mechanism provide a theoretical foundation for the control of the quadruped human-carrying walking chair robot.

Toward a Theory of Human Security

OpenAIRE

Tanaka, Akihiko

2015-01-01

“Human security” has occupied a significant place in the global discourses of peace, development, and diplomacy, despite often made criticisms of its conceptual ambiguity. Arguing for the merit of a broader definition of human security, i.e. “the right of people to live in freedom and dignity, free from poverty and despair” (UN Resolution A/RES/66/290), this paper offers an interdisciplinary theoretical framework in which key aspects of human security are systematically laid out: types of thr...

Studying Human Resource Information Systems Implementation using Adaptive Structuration Theory: The Case of an HRIS Implementation at Dow Chemical Company

NARCIS (Netherlands)

Ruel, Hubertus Johannes Maria; Chiemeke, Charles C.; Bondarouk, Tatiana; Ruel, Hubertus Johannes Maria; Guiderdoni-Jourdain, Karine; Oiry, Ewan

2009-01-01

Research on Human Resource Information Systems (HRIS) implementation lacks theoretical depth and richness. For that reason this paper applies a theory to HRIS implementation developed by Gerardine DeSanctis and Marshal Scott Poole originally for studying information systems implementation, namely

A conceptual framework for the integration of flow theory and cognitive evaluation theory

OpenAIRE

Abuhamdeh, Sami

2012-01-01

Flow theory (Csikszentmihalyi, Beyond boredom and anxiety: Experiencing flow in work and play. Jossey-Bass, San Francisco, 1975) and cognitive evaluation theory (Deci and Ryan, Intrinsic motivation and self-determination in human behaviour. Plenum, New York, 1985) have each inspired a large body of research dedicated to understanding why we enjoy doing what we enjoy doing. Although both theories ostensibly address the same category of behavior—namely, intrinsically motivated behavior—there ha...

Component Theories for Human Resource Development in China: A Proposition

Science.gov (United States)

Schmidtke, Carsten; Chen, Peng

2016-01-01

Chinese scholars have not yet achieved consensus on the specific theories that should be part of a Chinese HRD theory base. A review of the Chinese HRD literature has identified four theory domains frequently mentioned as a possible foundation for the discipline: management, economics, sociology, and psychology/learning. Considering Swanson and…

Communication theory

DEFF Research Database (Denmark)

Stein, Irene F.; Stelter, Reinhard

2011-01-01

Communication theory covers a wide variety of theories related to the communication process (Littlejohn, 1999). Communication is not simply an exchange of information, in which we have a sender and a receiver. This very technical concept of communication is clearly outdated; a human being...... is not a data processing device. In this chapter, communication is understood as a process of shared meaning-making (Bruner, 1990). Human beings interpret their environment, other people, and themselves on the basis of their dynamic interaction with the surrounding world. Meaning is essential because people...... ascribe specific meanings to their experiences, their actions in life or work, and their interactions. Meaning is reshaped, adapted, and transformed in every communication encounter. Furthermore, meaning is cocreated in dialogues or in communities of practice, such as in teams at a workplace or in school...

From Epicurus to Maslow: Happiness Then and Now and the Place of the Human Being in Social Theory

Directory of Open Access Journals (Sweden)

Gerald Gutenschwager

2013-05-01

Full Text Available Protagoras said, "The human being is the measure of all things". This implies, among other things, that language, science and religion are human inventions, as are economics, money, efficiency, race, conflict, etc. As symbol-using animals, we have created these concepts to serve our purposes. But as our societies have increased in size and our concepts have become more abstract, there is a danger that we will forget our authorship and reify these symbols. This inhibits change in the way we name things, so we are always in danger of misunderstanding the reality we are describing. We seem to be at such a stage now as we employ 18th and 19th century theories to describe and, more importantly, create 21st century reality. One such idea has to do with human needs. Influenced by the abstract (economic concepts we use, we have lost our sense of what we truly need. Epicurus and Maslow may help to review and reassess those concepts. Epicurus, by suggesting that our material needs are quite simple but that emotional and spiritual need satisfaction requires a small scale loving community, free from fear, and Maslow, by suggesting that our emotional development is age-related, which, besides therapy, may help in suggesting revisions in socioeconomic theory that would ensure the social conditions that would allow this development to take place successfully.

Livability theory

NARCIS (Netherlands)

R. Veenhoven (Ruut)

2014-01-01

markdownabstract__Abstract__ Assumptions Livability theory involves the following six key assumptions: 1. Like all animals, humans have innate needs, such as for food, safety, and companionship. 2. Gratification of needs manifests in hedonic experience. 3. Hedonic experience determines how

Impact of Artificial Intelligence on Economic Theory

OpenAIRE

Tshilidzi Marwala

2015-01-01

Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

Understanding human papillomavirus vaccination intentions: comparative utility of the theory of reasoned action and the theory of planned behavior in vaccine target age women and men.

Science.gov (United States)

Fisher, William A; Kohut, Taylor; Salisbury, Claire M A; Salvadori, Marina I

2013-10-01

Human papillomavirus (HPV) is an exceedingly prevalent sexually transmitted infection with serious medical, sexual, and relationship consequences. HPV vaccine protection is available but vaccine uptake is very inconsistent. This research applies two major theories of health behavior uptake, the Theory of Reasoned Action and the Theory of Planned Behavior, in an effort to understand intentions to receive HPV vaccine among vaccine target age women and men. The Theory of Reasoned Action asserts that attitudes toward HPV vaccination and perceptions of social support for HPV vaccination are the determinants of intentions to be vaccinated, whereas the Theory of Planned Behavior holds that attitudes toward vaccination, perceptions of social support for vaccination, and perceived ability to get vaccinated are the determinants of intentions to be vaccinated. Canadian university men (N=118) and women (N=146) in the HPV vaccine target age range took part in this correlational study online. Participants completed standard measures of attitudes toward HPV vaccination, perceptions of social support for vaccination, perceived ability to get vaccinated, beliefs about vaccination, and intentions to be vaccinated in the coming semester. Findings confirmed the propositions of the Theory of Reasoned Action and indicated that attitudes toward undergoing HPV vaccination and perceptions of social support for undergoing HPV vaccination contributed uniquely to the prediction of women's (R2=0.53) and men's (R2=0.44) intentions to be vaccinated in the coming semester. Clinical and public health education should focus on strengthening attitudes and perceptions of social support for HPV vaccination, and on the basic beliefs that appear to underlie attitudes and perceptions of social support for HPV vaccination, in efforts to promote HPV vaccine uptake. © 2013 International Society for Sexual Medicine.

Subcomponents and connectivity of the superior longitudinal fasciculus in the human brain.

Science.gov (United States)

Wang, Xuhui; Pathak, Sudhir; Stefaneanu, Lucia; Yeh, Fang-Cheng; Li, Shiting; Fernandez-Miranda, Juan C

2016-05-01

The subcomponents of the human superior longitudinal fasciculus (SLF) are disputed. The objective of this study was to investigate the segments, connectivity and asymmetry of the SLF. We performed high angular diffusion spectrum imaging (DSI) analysis on ten healthy adults. We also conducted fiber tracking on a 30-subject DSI template (CMU-30) and 488-subject template from the Human Connectome Project (HCP-488). In addition, five normal brains obtained at autopsy were microdissected. Based on tractography and microdissection results, we show that the human SLF differs significantly from that of monkey. The fibers corresponding to SLF-I found in 6 out of 20 hemispheres proved to be part of the cingulum fiber system in all cases and confirmed on both DSI and HCP-488 template. The most common patterns of connectivity bilaterally were as follows: from angular gyrus to caudal middle frontal gyrus and dorsal precentral gyrus representing SLF-II (or dorsal SLF), and from supramarginal gyrus to ventral precentral gyrus and pars opercularis to form SLF-III (or ventral SLF). Some connectivity features were, however, clearly asymmetric. Thus, we identified a strong asymmetry of the dorsal SLF (SLF-II), where the connectivity between the supramarginal gyrus with the dorsal precentral gyrus and the caudal middle frontal gyrus was only present in the left hemisphere. Contrarily, the ventral SLF (SLF-III) showed fairly constant connectivity with pars triangularis only in the right hemisphere. The results provide a novel neuroanatomy of the SLF that may help to better understand its functional role in the human brain.

Recognition-by-Components: A Theory of Human Image Understanding.

Science.gov (United States)

Biederman, Irving

1987-01-01

The theory proposed (recognition-by-components) hypothesizes the perceptual recognition of objects to be a process in which the image of the input is segmented at regions of deep concavity into an arrangement of simple geometric components. Experiments on the perception of briefly presented pictures support the theory. (Author/LMO)

Why did humans develop a large brain?

OpenAIRE

Muscat Baron, Yves

2012-01-01

"Of all animals, man has the largest brain in proportion to his size"- Aristotle. Dr Yves Muscat Baron shares his theory on how humans evolved large brains. The theory outlines how gravity could have helped humans develop a large brain- the author has named the theory 'The Gravitational Vascular Theory'. http://www.um.edu.mt/think/why-did-humans-develop-a-large-brain/

Quality of Malaysian Teachers Based on Education and Training: A Benefit and Earnings Returns Analysis Using Human Capital Theory

Science.gov (United States)

Ismail, Ramlee; Awang, Marinah

2017-01-01

Purpose: The purpose of this paper is to investigate how the quality of teachers based on education and training provided under new reform policies in Malaysia affects their earnings outcomes. The study conducted a benefit and returns analysis guided by human capital theory. Design/methodology/approach: The study used survey research methods to…

Serum BDNF correlates with connectivity in the (pre)motor hub in the aging human brain--a resting-state fMRI pilot study.

Science.gov (United States)

Mueller, Karsten; Arelin, Katrin; Möller, Harald E; Sacher, Julia; Kratzsch, Jürgen; Luck, Tobias; Riedel-Heller, Steffi; Villringer, Arno; Schroeter, Matthias L

2016-02-01

Brain-derived neurotrophic factor (BDNF) has been discussed to be involved in plasticity processes in the human brain, in particular during aging. Recently, aging and its (neurodegenerative) diseases have increasingly been conceptualized as disconnection syndromes. Here, connectivity changes in neural networks (the connectome) are suggested to be the most relevant and characteristic features for such processes or diseases. To further elucidate the impact of aging on neural networks, we investigated the interaction between plasticity processes, brain connectivity, and healthy aging by measuring levels of serum BDNF and resting-state fMRI data in 25 young (mean age 24.8 ± 2.7 (SD) years) and 23 old healthy participants (mean age, 68.6 ± 4.1 years). To identify neural hubs most essentially related to serum BDNF, we applied graph theory approaches, namely the new data-driven and parameter-free approach eigenvector centrality (EC) mapping. The analysis revealed a positive correlation between serum BDNF and EC in the premotor and motor cortex in older participants in contrast to young volunteers, where we did not detect any association. This positive relationship between serum BDNF and EC appears to be specific for older adults. Our results might indicate that the amount of physical activity and learning capacities, leading to higher BDNF levels, increases brain connectivity in (pre)motor areas in healthy aging in agreement with rodent animal studies. Pilot results have to be replicated in a larger sample including behavioral data to disentangle the cause for the relationship between BDNF levels and connectivity. Copyright © 2016 Elsevier Inc. All rights reserved.

Question of Drug Workers under the Prism Theory of Axel Honneth recognition . Human Right to Work and his pretension of Universal Validity

OpenAIRE

Maria Cecília Máximo Teodoro; Sabrina Colares Nogueira

2016-01-01

Relate the theme regarding the Theory of Recognition Axel Honnet, the human right to work as a human right to claim to universal validity, from the perspective of the Declaration of Fundamental Principles and Rights at Work ILO, for purposes of setting parameters and recognition of social (re) integration of chemical class dependent workers is the main goal of this article. We will analyze the theoretical framework in which the pursuit of human dignity at work is the goal of the state to whic...

Activity Theory

DEFF Research Database (Denmark)

Bertelsen, Olav Wedege; Bødker, Susanne

2003-01-01

the young HCI research tradition. But HCI was already facing problems: lack of consideration for other aspects of human behavior, for interaction with other people, for culture. Cognitive science-based theories lacked means to address several issues that came out of the empirical projects....

Systematic review of empiricism and theory in domestic minor sex trafficking research.

Science.gov (United States)

Twis, Mary K; Shelton, Beth Anne

2018-01-01

Empiricism and the application of human behavior theory to inquiry are regarded as markers of high-quality research. Unfortunately, scholars have noted that there are many gaps in theory and empiricism within the human trafficking literature, calling into question the legitimacy of policies and practices that are derived from the available data. To date, there has not been an analysis of the extent to which empirical methods and human behavior theory have been applied to domestic minor sex trafficking (DMST) research as a subcategory of human trafficking inquiry. To fill this gap in the literature, this systematic review was designed to assess the degree to which DMST publications are a) empirical, and b) apply human behavior theory to inquiry. This analysis also focuses on answering research questions related to patterns within DMST study data sources, and patterns of human behavior theory application. The results of this review indicate that a minority of sampled DMST publications are empirical, a minority of those articles that were empirical apply a specific human behavior theory within the research design and reporting of results, a minority of articles utilize data collected directly from DMST victims, and that there are no discernible patterns in the application of human behavior theory to DMST research. This research note suggests that DMST research is limited by the same challenges as the larger body of human trafficking scholarship. Based upon these overarching findings, specific recommendations are offered to DMST researchers who are committed to enhancing the quality of DMST scholarship.

Modularity, comparative cognition and human uniqueness.

Science.gov (United States)

Shettleworth, Sara J

2012-10-05

Darwin's claim 'that the difference in mind between man and the higher animals … is certainly one of degree and not of kind' is at the core of the comparative study of cognition. Recent research provides unprecedented support for Darwin's claim as well as new reasons to question it, stimulating new theories of human cognitive uniqueness. This article compares and evaluates approaches to such theories. Some prominent theories propose sweeping domain-general characterizations of the difference in cognitive capabilities and/or mechanisms between adult humans and other animals. Dual-process theories for some cognitive domains propose that adult human cognition shares simple basic processes with that of other animals while additionally including slower-developing and more explicit uniquely human processes. These theories are consistent with a modular account of cognition and the 'core knowledge' account of children's cognitive development. A complementary proposal is that human infants have unique social and/or cognitive adaptations for uniquely human learning. A view of human cognitive architecture as a mosaic of unique and species-general modular and domain-general processes together with a focus on uniquely human developmental mechanisms is consistent with modern evolutionary-developmental biology and suggests new questions for comparative research.

Question of Drug Workers under the Prism Theory of Axel Honneth recognition . Human Right to Work and his pretension of Universal Validity

Directory of Open Access Journals (Sweden)

Maria Cecília Máximo Teodoro

2016-06-01

Full Text Available Relate the theme regarding the Theory of Recognition Axel Honnet, the human right to work as a human right to claim to universal validity, from the perspective of the Declaration of Fundamental Principles and Rights at Work ILO, for purposes of setting parameters and recognition of social (re integration of chemical class dependent workers is the main goal of this article. We will analyze the theoretical framework in which the pursuit of human dignity at work is the goal of the state to which we treat below the dignity of man as a right whose claim to universal validity is based on the recognition of the theory of Axel Honneth . That said, we analyze the possible dignity of man at work in a global context from the recognition of new rights, especially with regard to the category of workers who occupy the social portion of chemical-dependent, whose participation in the social process is prevented, creating a category of workers socially excluded, which is intended to overcome.

Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views.

Science.gov (United States)

Sutterer, Matthew J; Tranel, Daniel

2017-11-01

We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Pro-cognitive drug effects modulate functional brain network organization

Science.gov (United States)

Giessing, Carsten; Thiel, Christiane M.

2012-01-01

Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with functional magnetic resonance imaging (fMRI). Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e., the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the “global workspace” theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs

Justice relations as determinative factor of “human - state” relation in the J.Rawls’s theory

Directory of Open Access Journals (Sweden)

Z. O. Burychko

2014-04-01

Full Text Available The conceptualization of relations “human ­ state” in J. Rawls’s theory is revealed in the article. It is concluded, that this relationship is determineted on value level by justice, which understands as fairness. Justice is the main virtue of social institutions, and in this case, if the institutions are unjust, their activity should be discarded or revised. Based on liberal ideas, justice linked to the notion of freedom, particularly in J. Rawls’s theory are described? That in the faire societies the equal freedom of citizens is regarded as being established beforehand state. The main principles of relations are the principle of participation and paternalism. Participation means the involvement of citizens in the constitutional process, the national process and participation in self­government. Paternalism is understood as the rational intervention of state in society in aim to prevent irrational expressions of relations between people. Conditions intervention: it must be justified by the apparent inability or lack of will; must match the understanding of justice as fairness, and based on sustainable interests. It is concluded, that the theory of J. Rawls resulting from the analytical experiment leaves a lot of questions as to achieve justice as fairness in the activities of individuals and social institutions.

Toward a Unified Theory of Work: Organizational Simulations and Policy Analyses

National Research Council Canada - National Science Library

Vaughan, David

2002-01-01

.... This unified theory of work will connect theories of human traits and states, theories of task and job characteristics, theories of job/task performance, and perhaps theories of organizational behavior...

Theorising big IT programmes in healthcare: strong structuration theory meets actor-network theory.

Science.gov (United States)

Greenhalgh, Trisha; Stones, Rob

2010-05-01

The UK National Health Service is grappling with various large and controversial IT programmes. We sought to develop a sharper theoretical perspective on the question "What happens - at macro-, meso- and micro-level - when government tries to modernise a health service with the help of big IT?" Using examples from data fragments at the micro-level of clinical work, we considered how structuration theory and actor-network theory (ANT) might be combined to inform empirical investigation. Giddens (1984) argued that social structures and human agency are recursively linked and co-evolve. ANT studies the relationships that link people and technologies in dynamic networks. It considers how discourses become inscribed in data structures and decision models of software, making certain network relations irreversible. Stones' (2005) strong structuration theory (SST) is a refinement of Giddens' work, systematically concerned with empirical research. It views human agents as linked in dynamic networks of position-practices. A quadripartite approcach considers [a] external social structures (conditions for action); [b] internal social structures (agents' capabilities and what they 'know' about the social world); [c] active agency and actions and [d] outcomes as they feed back on the position-practice network. In contrast to early structuration theory and ANT, SST insists on disciplined conceptual methodology and linking this with empirical evidence. In this paper, we adapt SST for the study of technology programmes, integrating elements from material interactionism and ANT. We argue, for example, that the position-practice network can be a socio-technical one in which technologies in conjunction with humans can be studied as 'actants'. Human agents, with their complex socio-cultural frames, are required to instantiate technology in social practices. Structurally relevant properties inscribed and embedded in technological artefacts constrain and enable human agency. The fortunes

Path-Goal Theory of Leadership

Science.gov (United States)

1975-04-01

Leadership and Turnover Among Managers ," Organization Behavior and Human Performance, 10(1973), pp. 184-200; R. J. House, "A Path-Goal Theory of...of Leadership ." 6R. J. House and G. Dessler, "Path-Goal Theory of Leadership " R. M. Stqg- dill. Managers , Employees, Organization (Ohio State...of Control." 23 R. J. House, "Notes on the Path-Goal Theory of Leadership " (University of Toronto, Faculty of Management Studies, May 1974). 24 R

Temporal slice registration and robust diffusion-tensor reconstruction for improved fetal brain structural connectivity analysis.

Science.gov (United States)

Marami, Bahram; Mohseni Salehi, Seyed Sadegh; Afacan, Onur; Scherrer, Benoit; Rollins, Caitlin K; Yang, Edward; Estroff, Judy A; Warfield, Simon K; Gholipour, Ali

2017-08-01

Diffusion weighted magnetic resonance imaging, or DWI, is one of the most promising tools for the analysis of neural microstructure and the structural connectome of the human brain. The application of DWI to map early development of the human connectome in-utero, however, is challenged by intermittent fetal and maternal motion that disrupts the spatial correspondence of data acquired in the relatively long DWI acquisitions. Fetuses move continuously during DWI scans. Reliable and accurate analysis of the fetal brain structural connectome requires careful compensation of motion effects and robust reconstruction to avoid introducing bias based on the degree of fetal motion. In this paper we introduce a novel robust algorithm to reconstruct in-vivo diffusion-tensor MRI (DTI) of the moving fetal brain and show its effect on structural connectivity analysis. The proposed algorithm involves multiple steps of image registration incorporating a dynamic registration-based motion tracking algorithm to restore the spatial correspondence of DWI data at the slice level and reconstruct DTI of the fetal brain in the standard (atlas) coordinate space. A weighted linear least squares approach is adapted to remove the effect of intra-slice motion and reconstruct DTI from motion-corrected data. The proposed algorithm was tested on data obtained from 21 healthy fetuses scanned in-utero at 22-38 weeks gestation. Significantly higher fractional anisotropy values in fiber-rich regions, and the analysis of whole-brain tractography and group structural connectivity, showed the efficacy of the proposed method compared to the analyses based on original data and previously proposed methods. The results of this study show that slice-level motion correction and robust reconstruction is necessary for reliable in-vivo structural connectivity analysis of the fetal brain. Connectivity analysis based on graph theoretic measures show high degree of modularity and clustering, and short average

Power, trust, and Science of Unitary Human Beings influence political leadership: a celebration of Barrett's power theory.

Science.gov (United States)

Wright, Barbara W

2010-01-01

The importance of nurses' participation in health policy leadership is discussed within the context of Rogers' science of unitary human beings, Barrett's power theory, and one nurse-politician's experience. Nurses have a major role to play in resolving public policy issues that influence the health of people. A brief review of the history of nurses in the political arena is presented. Research related to power and trust is reviewed. Suggested strategies for success in political situations are offered.

The Form of HWID Theory

DEFF Research Database (Denmark)

Clemmensen, Torkil

2015-01-01

The aim of activities within the Human-Computer Interaction (HCI) area named Human Work Interaction Design (HWID) is to establish relationships between empirical work-domain studies and recent developments in interaction design. Recent areas of research within HWID include design sketches for work......, usability in context, work analysis for HCI, and integration of work analysis and interaction design methods for pervasive and smart workplaces. Across these areas, the question emerges what form of theory may HWID research produce? The aim with this paper is to investigate the requirements of different...... research purposes to a common framework. We take the position that we should approach HWID with a lightweight, medium-level framework that is useful to guide the application of other theories to study the relation between work analysis and interaction design. We analyse the requirements to theory found...

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

Science.gov (United States)

Bassett, Danielle S; Mattar, Marcelo G

2017-04-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

The quartet theory: Implications for autism spectrum disorder. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

Science.gov (United States)

Pehrs, Corinna; Samson, Andrea C.; Gross, James J.

2015-06-01

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social and communication deficits as well as restricted and repetitive behaviors [1]. Specific deficits include failure to initiate reciprocal social interactions, verbal and non-verbal communication difficulties, decreased sensitivity to social and emotional cues, and limited perspective-taking abilities. Social withdrawal, avoidance or indifference to affection or physical contact, lack of eye contact, and decreased joint attention and facial responsiveness are also common [2]. In addition to these core features, there is a growing body of literature that describes problematic patterns of emotional reactivity (increased negative and decreased positive emotions) and emotion regulation (increased use of maladaptive and decreased use of adaptive emotion regulation strategies) [3-5]. The present comment seeks to link difficulties in socio-emotional domains to the Quartet Theory of Human Emotions by mapping characteristic ASD social deficits and emotion dysregulation onto two of the affect systems described in this theory: the hippocampal and orbitofrontal-centered systems.

Paradigm Shift in Game Theory: Sociological Re-Conceptualization of Human Agency, Social Structure, and Agents’ Cognitive-Normative Frameworks and Action Determination Modalities

Directory of Open Access Journals (Sweden)

Tom R. Burns

2018-03-01

Full Text Available This article aims to present some of the initial work of developing a social science grounded game theory—as a clear alternative to classical game theory. Two distinct independent initiatives in Sociology are presented: One, a systems approach, social systems game theory (SGT, and the other, Erving Goffman’s interactionist approach (IGT. These approaches are presented and contrasted with classical theory. They focus on the social rules, norms, roles, role relationships, and institutional arrangements, which structure and regulate human behavior. While strategic judgment and instrumental rationality play an important part in the sociological approaches, they are not a universal or dominant modality of social action determination. Rule following is considered, generally speaking, more characteristic and more general. Sociological approaches, such as those outlined in this article provide a language and conceptual tools to more adequately and effectively than the classical theory describe, model, and analyze the diversity and complexity of human interaction conditions and processes: (1 complex cognitive rule based models of the interaction situation with which actors understand and analyze their situations; (2 value complex(es with which actors operate, often with multiple values and norms applying in interaction situations; (3 action repertoires (rule complexes with simple and complex action alternatives—plans, programs, established (sometimes highly elaborated algorithms, and rituals; (4 a rule complex of action determination modalities for actors to generate and/or select actions in game situations; three action modalities are considered here; each modality consists of one or more procedures or algorithms for action determination: (I following or implementing a rule or rule complex, norm, role, ritual, or social relation; (II selecting or choosing among given or institutionalized alternatives according to a rule or principle; and (III

Integrative Literature Review: Concept Mapping--A Strategy to Support the Development of Practice, Research, and Theory within Human Resource Development

Science.gov (United States)

Daley, Barbara J.; Conceicao, Simone C. O.; Mina, Liliana; Altman, Brian A.; Baldor, Maria; Brown, James

2010-01-01

The purpose of this integrative literature review is to summarize research on concept mapping and to offer ideas on how concept mapping can facilitate practice, research, and theory development within human resource development. In this review, more than 300 articles, written in both English and Spanish, presented at two different concept mapping…

Client-controlled case information: a general system theory perspective.

Science.gov (United States)

Fitch, Dale

2004-07-01

The author proposes a model for client control of case information via the World Wide Web built on principles of general system theory. It incorporates the client into the design, resulting in an information structure that differs from traditional human services information-sharing practices. Referencing general system theory, the concepts of controller and controlled system, as well as entropy and negentropy, are applied to the information flow and autopoietic behavior as they relate to the boundary-maintaining functions of today's organizations. The author's conclusions synthesize general system theory and human services values to lay the foundation for an information-sharing framework for human services in the 21st century.

[The medical theory of Lee Je-ma and its character].

Science.gov (United States)

Lee, Kyung-Lock

2005-12-01

Lee Je-ma 1837-1900) was a prominent scholar as well as an Korean physician. classified every people into four distinctive types: greater yang [tai yang] person, lesser yin [shao yin] person, greater yin [tai yin] person, lesser yin [shao yin] person. This theory would dictate proper treatment for each type in accordance with individual differences of physical and temperament features. Using these four types he created The Medical Science of Four Types. This article is intended to look into the connection between Lee Je-Ma's 'The Medical Science of Four Types' and 'The Modern' with organizing his ideas about the human body and the human being. Through The Modern, the theory of human being underwent a complete change. Human being in The Premodern, which was determined by sex, age and social status has been changed to the individual human being, which is featured by equality. Lee Je-Ma's medical theory of The Medical Science of Four Types would be analyzed as follow. His concept of human body is oriented toward observable objectivity. But on the other hand, it still remains transcendent status of medical science, which is subordinated by philosophy. According to Lee Je-Ma's theory of human being, human is an equal individual in a modern way of thinking, not as a part of hierarchical group. But on the other hand, it still remains incomplete from getting rid of morality aspect that includes virtue and vice in the concept of human body. The common factors in Lee Je-Ma's ideas about the human body and the human being is 'Dualism of mind and body that means all kinds of status and results depends on each individual. As is stated above, Lee Je-Ma's medical theory has many aspects of The Modern and it proves that Korean traditional medicine could be modernized by itself.

White matter integrity in brain networks relevant to anxiety and depression: evidence from the human connectome project dataset.

Science.gov (United States)

De Witte, Nele A J; Mueller, Sven C

2017-12-01

Anxiety and depression are associated with altered communication within global brain networks and between these networks and the amygdala. Functional connectivity studies demonstrate an effect of anxiety and depression on four critical brain networks involved in top-down attentional control (fronto-parietal network; FPN), salience detection and error monitoring (cingulo-opercular network; CON), bottom-up stimulus-driven attention (ventral attention network; VAN), and default mode (default mode network; DMN). However, structural evidence on the white matter (WM) connections within these networks and between these networks and the amygdala is lacking. The current study in a large healthy sample (n = 483) observed that higher trait anxiety-depression predicted lower WM integrity in the connections between amygdala and specific regions of the FPN, CON, VAN, and DMN. We discuss the possible consequences of these anatomical alterations for cognitive-affective functioning and underscore the need for further theory-driven research on individual differences in anxiety and depression on brain structure.

Aesthetic emotions goals. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

Science.gov (United States)

Perlovsky, Leonid

2015-06-01

Review by Koelsch et al. [10] presents an interdisciplinary theory of emotions, including a neurobiological emotion theory originating in four core emotional systems. The Quartet Theory (QT) includes specifically human emotions and considers the role of language for emotions. This comment considers questions about how the QT can address aesthetic emotions, what class of emotions they are, and what their function in cognition is. Can QT help defining aesthetic emotions neurally and functionally? Such a definition of aesthetic emotions would be necessary for their scientific exploration, because as widely used today there is no definition, aesthetics is defined through art, and art through aesthetics. Since contents of many art museums are not accepted as art by many artists and admirers of art, it is not clear what should be the subject of aesthetic emotions research.

Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex.

Science.gov (United States)

Yeo, B T Thomas; Krienen, Fenna M; Chee, Michael W L; Buckner, Randy L

2014-03-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. © 2013.

Segmentation of the Cingulum Bundle in the Human Brain: A New Perspective Based on DSI Tractography and Fiber Dissection Study.

Science.gov (United States)

Wu, Yupeng; Sun, Dandan; Wang, Yong; Wang, Yibao; Ou, Shaowu

2016-01-01

The cingulum bundle (CB) is a critical white matter fiber tract in the brain, which forms connections between the frontal lobe, parietal lobe and temporal lobe. In non-human primates, the CB is actually divided into distinct subcomponents on the basis of corticocortical connections. However, at present, no study has verified similar distinct subdivisions in the human brain. In this study, we reconstructed these distinct subdivisions in the human brain, and determined their exact cortical connections using high definition fiber tracking (HDFT) technique on 10 healthy adults and a 488-subject template from the Human Connectome Project (HCP-488). Fiber dissections were performed to verify tractography results. Five CB segments were identified. CB-I ran from the subrostral areas to the precuneus and splenium, encircling the corpus callosum (CC). CB-II arched around the splenium and extended anteriorly above the CC to the medial aspect of the superior frontal gyrus (SFG). CB-III connected the superior parietal lobule (SPL) and precuneus with the medial aspect of the SFG. CB-IV was a relatively minor subcomponent from the SPL and precuneus to the frontal region. CB-V, the para-hippocampal cingulum, stemmed from the medial temporal lobe and fanned out to the occipital lobes. Our findings not only provide a more accurate and detailed description on the associated architecture of the subcomponents within the CB, but also offer new insights into the functional role of the CB in the human brain.

Segmentation of the cingulum bundle in the human brain: a new perspective based on DSI tractography and fiber dissection study

Directory of Open Access Journals (Sweden)

Yupeng Wu

2016-09-01

Full Text Available The cingulum bundle (CB is a critical white matter fiber tract in the brain, which forms connections between the frontal lobe, parietal lobe, and temporal lobe. In non-human primates, the CB is actually divided into distinct subcomponents on the basis of corticocortical connections. However, at present, no study has verified similar distinct subdivisions in the human brain. In this study, we reconstructed these distinct subdivisions in the human brain, and determined their exact cortical connections using high definition fiber tracking (HDFT technique on 10 healthy adults and a 488-subject template from the Human Connectome Project (HCP-488. Fiber dissections were performed to verify tractography results. Five CB segments were identified. CB-I ran from the subrostral areas to the precuneus and splenium, encircling the corpus callosum. CB-II arched around the splenium and extended anteriorly above the corpus callosum to the medial aspect of the superior frontal gyrus. CB-III connected the superior parietal lobule and precuneus with the medial aspect of the superior frontal gyrus. CB-IV was a relatively minor subcomponent from the superior parietal lobule and precuneus to the frontal region. CB-V, the para-hippocampal cingulum, stemmed from the medial temporal lobe and fanned out to the occipital lobes. Our findings not only provide a more accurate and detailed description on the associated architecture of the subcomponents within the CB, but also offer new insights into the functional role of the CB in the human brain.

Transformative Theory in Social Research

DEFF Research Database (Denmark)

Ravn, Ib

Social-scientific theory usually represents an attempt to describe or explain social phenomena and, sometimes, to criticize them. However, a theory can be transformative in the sense that in using and testing it, researchers may help practitioners transform and improve their social conditions......, institutions or organisations. This idea is illustrated by a research-and-development effort to help conference organisers develop meeting formats that create more learning among delegates than is accomplished by the conventional, lecture-based format. This effort was based on a (transformative) theory...... of conferences as forums for learning and "human co-flourishing." Seventeen learning techniques were derived from the theory and were tested as hypotheses: When implemented in 30 live experiments, did they contribute to learning, as specified by the theory? Properties of transformative theory that distinguish...

Defamation of Religions: A Vague and Overbroad Theory that Threatens Basic Human Rights

Directory of Open Access Journals (Sweden)

Allison G. Belnap

2011-04-01

Full Text Available Il contributo è pubblicato con il permesso della Brigham Young University Law Review - dove è apparso nel vol. n. 2 del 2010 (Tribute to Professor Michael Goldsmith, alle pp. 101-148 - e dell‖Autrice, che ringraziamo sentitamente. SUMMARY: 1. Introduction - 2. History of and Motivations for the OIC Defamation of Religions Resolutions - 2.a - The OIC Exerts a Concerted Effort to Protect Islam - 2.b - Terrorist Attacks and Danish Cartoons Raise the Stakes - 3. Defamation of Religions: A Permissible Restraint on Freedom of Speech and Expression? - 3.a - History, Basic Elements, and Contemporary Usage of Defamation - 3.b - Interaction Between Defamation of Religions and the Basic Human Rights Enumerated in Major International Instruments - 4. The Evolution of a Resolution - 4.a. 1999-2000: Beginnings - 4.b. 2001: A Pre-9/11 World - 4.c. 2002: Reactions to the Violent Backlash Against Muslims - 4.d. 2003-2004: Fluctuations in Support - 4.e. 2005: Intensification of a Campaign - 4.f. 2006-2007: The Move to the General Assembly - 4.g. 2008: Decreasing Margins of Support - 4.h. 2009: Current Resolution and Recommendations for Application - 5. Consequences of Accepting the Resolutions and Subsequent Enactment of Statutes Designed to Prevent Defamation of Religions - 5.a. Human Rights Committee - 5.b. The European Court of Human Rights - 5.c. Blasphemy, Incitement, and Hate Speech Laws and Their Enforcement - 5.d. Possible Future Statutes and Enforcement Under Defamation of Religions Theory - 6. Alternatives to Defamation of Religions in the U.N. Resolutions - 7. Conclusion.

Implausibility of the vibrational theory of olfaction.

Science.gov (United States)

Block, Eric; Jang, Seogjoo; Matsunami, Hiroaki; Sekharan, Sivakumar; Dethier, Bérénice; Ertem, Mehmed Z; Gundala, Sivaji; Pan, Yi; Li, Shengju; Li, Zhen; Lodge, Stephene N; Ozbil, Mehmet; Jiang, Huihong; Penalba, Sonia F; Batista, Victor S; Zhuang, Hanyi

2015-05-26

The vibrational theory of olfaction assumes that electron transfer occurs across odorants at the active sites of odorant receptors (ORs), serving as a sensitive measure of odorant vibrational frequencies, ultimately leading to olfactory perception. A previous study reported that human subjects differentiated hydrogen/deuterium isotopomers (isomers with isotopic atoms) of the musk compound cyclopentadecanone as evidence supporting the theory. Here, we find no evidence for such differentiation at the molecular level. In fact, we find that the human musk-recognizing receptor, OR5AN1, identified using a heterologous OR expression system and robustly responding to cyclopentadecanone and muscone, fails to distinguish isotopomers of these compounds in vitro. Furthermore, the mouse (methylthio)methanethiol-recognizing receptor, MOR244-3, as well as other selected human and mouse ORs, responded similarly to normal, deuterated, and (13)C isotopomers of their respective ligands, paralleling our results with the musk receptor OR5AN1. These findings suggest that the proposed vibration theory does not apply to the human musk receptor OR5AN1, mouse thiol receptor MOR244-3, or other ORs examined. Also, contrary to the vibration theory predictions, muscone-d30 lacks the 1,380- to 1,550-cm(-1) IR bands claimed to be essential for musk odor. Furthermore, our theoretical analysis shows that the proposed electron transfer mechanism of the vibrational frequencies of odorants could be easily suppressed by quantum effects of nonodorant molecular vibrational modes. These and other concerns about electron transfer at ORs, together with our extensive experimental data, argue against the plausibility of the vibration theory.

The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine

OpenAIRE

Wolff, J Gerard

2016-01-01

This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence. The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from...

The impact of stroke aphasia on health and well-being and appropriate nursing interventions: an exploration using the Theory of Human Scale Development.

Science.gov (United States)

Thompson, Juliana; McKeever, Margo

2014-02-01

This paper considers the impact of aphasia on health and well-being and provides suggestions for appropriate nursing interventions. Background.  Effective communication is essential to holistic care and positive outcomes for individuals affected by aphasia. When verbal communication is absent, nurses fail to adequately use alternative strategies so that the standard of nurse/patient communication is frequently poor. This is a discursive paper which reviews relevant literature and uses the Theory of Human Scale Development as a framework for discussion. The Theory of Human Scale Development is introduced. This theory emphasises that quality of life depends as much upon self-actualisation and relation building as on physical health. The theory is used within the discussion to highlight the significance of communication to quality of life and how its loss has profound psychological and social consequences. Aphasia results in 'loss of self'. The situation is exacerbated by inadequate healthcare communication strategies. Suggestions are offered regarding more appropriate strategies. Efficacy of family input is considered; nursing competence regarding language practice therapies is discussed, and the 'quest approach' is explored. Aphasia has a negative impact on relationships by denying access to support networks, which results in isolation. The individual's predicament is worsened by negative nursing responses. Positive nursing strategies, which alleviate effects of aphasia on individuals' social health, are investigated. Concept analysis and self-awareness exercises as methods of enhancing compassion skills are explored. The social model of disability is discussed to highlight the benefits to individuals of environmental adaptations. The social benefits of aphasia-group affiliation are discussed. The paper concludes by emphasising that fundamental human needs involve social and psychological as well as physical aspects. Nursing interventions must address all needs to

The teaching theory of Montaigne

Directory of Open Access Journals (Sweden)

José PENALVA BUITRAGO

2013-11-01

Full Text Available This article seeks to articulate the teaching theory of Montaigne. The core idea is that Montaigne’s thought, founded on formation classical ideal, is based on basic belief about the confidence in man, confidence in humanity possibilities to release from the weakness and frauds of the mind, to be a real man. The author develops the idea along these three lines: firstly, anthropology theory that inspires the educational theory of Montaigne; secondly, the anthropology values that we need to became a real man; and thirdly, the teaching process and the relationship with the teacher. Finally, in conclusion, the author shows a articulation of the tea- ching theory.

Theory of mind and Verstehen (understanding) methodology.

Science.gov (United States)

Kumazaki, Tsutomu

2016-09-01

Theory of mind is a prominent, but highly controversial, field in psychology, psychiatry, and philosophy of mind. Simulation theory, theory-theory and other views have been presented in recent decades, none of which are monolithic. In this article, various views on theory of mind are reviewed, and methodological problems within each view are investigated. The relationship between simulation theory and Verstehen (understanding) methodology in traditional human sciences is an intriguing issue, although the latter is not a direct ancestor of the former. From that perspective, lessons for current clinical psychiatry are drawn. © The Author(s) 2016.

Smith’s theory of wages and its impact on the theory of wages in the 19th century

Directory of Open Access Journals (Sweden)

Stojanović Božo

2005-01-01

Full Text Available Adam Smith has not accepted subsistence theory of wages as an explanation of wages. He can be marked not only as a founder of wages-fund theory, but also of the bargaining theory of wages. Wage-fund doctrine dominated the next hundred years of English economics. Besides, Smith’s explanation of the differentials in wage rates among occupations were accepted by his successors for a century. That was the first step into direction of human capital theory.

What is reconfigured?. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

Science.gov (United States)

Engelen, Eva-Maria

2015-06-01

The research group around Koelsch presents a neurobiological emotion theory that is supposed to have the following plus factors: (1) Interdisciplinary approach towards understanding human emotions and their neural correlates, (2) concentration on human emotions, (3) interaction between language and emotion, (4) allows research on short-term emotional phenomena and takes long-term emotional phenomena into account, as well as the differences of the neural correlates underlying short-term and long-term emotions [5]. This is a very ambitious program. My comment will focus on (3) and (4).

Learning Theories In Instructional Multimedia For English Learning

OpenAIRE

Farani, Rizki

2016-01-01

Learning theory is the concept of human learning. This concept is one of the important components in instructional for learning, especially English learning. English subject becomes one of important subjects for students but learning English needs specific strategy since it is not our vernacular. Considering human learning process in English learning is expected to increase students' motivation to understand English better. Nowadays, the application of learning theories in English learning ha...

Post-Colonial Theory and Action Research

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Jim Parsons

2011-02-01

Full Text Available This essay explores connections between post-colonial theory and action research. Post-colonial theory is committed to addressing the plague of colonialism. Action research, at its core, promises to problematize uncontested ‘colonial’ hegemonies of any form. Both post-colonial theory and action research engage dialogic, critically reflective and collaborative values to offer a fuller range of human wisdom. The authors contend that post-colonialism theory calls for justice and seeks to speak to social and psychological suffering, exploitation, violence and enslavement done to the powerless victims of colonization around the world by challenging the superiority of dominant perspectives and seeking to re-position and empower the marginalized and subordinated. In similar ways, action research works to eradicate oppression, powerlessness and worthlessness by affirming solidarity with the oppressed, helping humans move from passive to active and by fundamentally reshaping power. Because both post-colonial theory and action research position the insider or oppressed in an ethic of efficacy, it values community, relationships, communication and equality, and is committed to reciprocity, reflexivity and reflection. Thus, both hold the potential to help reconstruct conditions for a more democratic and just society

Post-Colonial Theory and Action Research

Directory of Open Access Journals (Sweden)

Jim B. Parsons

2011-04-01

Full Text Available This essay explores connections between post-colonial theory and action research. Post-colonial theory is committed to addressing the plague of colonialism. Action research, at its core, promises to problematize uncontested ‘colonial’ hegemonies of any form. Both post-colonial theory and action research engage dialogic, critically reflective and collaborative values to offer a fuller range of human wisdom. The authors contend that post-colonialism theory calls for justice and seeks to speak to social and psychological suffering, exploitation, violence and enslavement done to the powerless victims of colonization around the world by challenging the superiority of dominant perspectives and seeking to re-position and empower the marginalized and subordinated. In similar ways, action research works to eradicate oppression, powerlessness and worthlessness by affirming solidarity with the oppressed, helping humans move from passive to active and by fundamentally reshaping power. Because both post-colonial theory and action research position the insider or oppressed in an ethic of efficacy, it values community, relationships, communication and equality, and is committed to reciprocity, reflexivity and reflection. Thus, both hold the potential to help reconstruct conditions for a more democratic and just society.

Moral Theories and Cloning in Kazuo Ishiguro’s Never Let Me Go

OpenAIRE

Petrillo, Stephanie

2014-01-01

In this paper I will consider the ethics of cloning as it occurs in Kazuo Ishiguro’s dystopian novel Never Let Me Go from the standpoint of a number of moral theories – consequentialism, natural law theory, Kantian moral theory, rights based theory, and virtue ethics. In light of the moral theories, I will develop an analysis for why cloning-for-biomedical-research as outlined in the 2002 document Human Cloning and Human Dignity by the President’s Council on Bioethics is morally permissible, ...

Health and welfare in animals and humans.

Science.gov (United States)

Nordenfelt, Lennart

2011-06-01

This paper contains a brief comparative analysis of some philosophical and scientific discourses on human and animal health and welfare, focusing mainly on the welfare of sentient animals. The paper sets forth two kinds of proposals for the analysis of animal welfare which do not appear in the contemporary philosophical discussion of human welfare, viz. the coping theory of welfare and the theory of welfare in terms of natural behaviour. These proposals are scrutinized in the light of some similar theories dealing with human health and quality of life. My conclusion is that the coping theory and the natural behaviour theory are not in themselves adequate for the characterization of welfare, either for humans or for sentient animals. I contend, finally, that, in the light of the previous discussion, there are good arguments for a particular set of analyses of both animal and human welfare, viz. the ones that are based on the notions of preference satisfaction and positive subjective experiences.

Evolutionary game theory meets social science: is there a unifying rule for human cooperation?

Science.gov (United States)

Rosas, Alejandro

2010-05-21

Evolutionary game theory has shown that human cooperation thrives in different types of social interactions with a PD structure. Models treat the cooperative strategies within the different frameworks as discrete entities and sometimes even as contenders. Whereas strong reciprocity was acclaimed as superior to classic reciprocity for its ability to defeat defectors in public goods games, recent experiments and simulations show that costly punishment fails to promote cooperation in the IR and DR games, where classic reciprocity succeeds. My aim is to show that cooperative strategies across frameworks are capable of a unified treatment, for they are governed by a common underlying rule or norm. An analysis of the reputation and action rules that govern some representative cooperative strategies both in models and in economic experiments confirms that the different frameworks share a conditional action rule and several reputation rules. The common conditional rule contains an option between costly punishment and withholding benefits that provides alternative enforcement methods against defectors. Depending on the framework, individuals can switch to the appropriate strategy and method of enforcement. The stability of human cooperation looks more promising if one mechanism controls successful strategies across frameworks. Published by Elsevier Ltd.

The bounds of reason game theory and the unification of the behavioral sciences

CERN Document Server

Gintis, Herbert

2014-01-01

Game theory is central to understanding human behavior and relevant to all of the behavioral sciences-from biology and economics, to anthropology and political science. However, as The Bounds of Reason demonstrates, game theory alone cannot fully explain human behavior and should instead complement other key concepts championed by the behavioral disciplines. Herbert Gintis shows that just as game theory without broader social theory is merely technical bravado, so social theory without game theory is a handicapped enterprise. This edition has been thoroughly revised and updated. Reinvigorati

The development of the five mini-theories of self-determination theory: an historical overview, emerging trends, and future directions

OpenAIRE

Vansteenkiste, Maarten; Niemiec, Christopher P; Soenens, Bart

2010-01-01

Self-determination theory is a macro-theory of human motivation, emotion, and personality that has been under development for 40 years following the seminal work of Edward Deci and Richard Ryan. Self-determination theory (SDT; Deci & Ryan, 1985b, 2000; Niemiec, Ryan, & Deci, in press; Ryan & Deci, 2000; Vansteenkiste, Ryan, & Deci, 2008) has been advanced in a cumulative, research-driven manner, as new ideas have been naturally and steadily integrated into the theory following sufficient empi...

Two theories on the test bench: Internal and external validity of the theories of Ronald Inglehart and Shalom Schwartz

OpenAIRE

Datler, Georg; Jagodzinski, Wolfgang; Schmidt, Peter

2013-01-01

In the last decades value research has produced a vast number of theoretical concepts. However, it is unclear how the different value theories relate to each other. This study makes a first step toward a systematic comparison of value theories. It focuses on the individual level of the two approaches that are, at present, probably the most prominent in international research - the theory of basic human values of Shalom Schwartz and the postmodernization theory of Ronald Inglehart. Using data ...

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

OpenAIRE

Rosenberg, Monica D.; Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

2016-01-01

Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained...

Organizational Behaviour in 21st Century – ‘Theory A’ for Managing People for Performance

OpenAIRE

Aithal, Sreeramana; Kumar, Suresh

2016-01-01

Theory X, Theory Y and Theory Z in organizational behaviour (OB) are related to human motivation and management. Theory X and Y were coined by Douglas McGregor in the late 1960s, says that the average human being is lazy and self-centred, lacks ambition, dislikes change, and longs to be told what to do. The corresponding managerial approach emphasizes total control. Theory Y maintains that human beings are active rather than passive shapers of themselves and of their environment. They long to...

The medical theory of Lee Je-ma and its character

Directory of Open Access Journals (Sweden)

LEE Kyung-Lock

2005-12-01

Full Text Available Lee Je-ma(李濟馬, 1837-1900 was a prominent scholar as well as an Korean physician He classified every people into four distinctive types: greater yang[tai yang] person, lesser yin[shao yin] person greater yin[tai yin] person, lesser yin[shao yin] person. This theory would dictate proper treatment for each type in accordance with individual differences of physical and temperament features Using these four types he created The Medical Science of Four Types(四象體質論.This article is intended to look into the connection between Lee Je-Ma's 'The Medical Science of Four Types' and 'The Modern' with organizing his ideas about the human body and the human being. Through The Modern, the theory of human being(人間觀 underwent a complete change. Human being in The Premodern, which was determined by sex, age and social status has been changed to the individual human being, which is featured by equality. Lee Je-Ma's medical theory of The Medical Science of Four Types would be analyzed as follow. His concept of human body(人體論 is oriented toward observable objectivity. But on the other hand, it still remains transcendent status of medical science, which is subordinated by philosophy According to Lee Je-Ma's theory of human being human is an equal individual in a modern way of thinking not as a part of hierarchical group. But on the other hand, it still remains incomplete from getting rid of morality aspect that includes virtue and vice in the concept of human body.The common factors in Lee Je-Ma's ideas about the human body and the human being is 'Dualism of mind and body(心身二元論' that means all kinds of status and results depends on each individual. As is stated above, Lee Je-Ma's medical theory has many aspects of The Modern and it proves that Korean traditional medicine could be modernized by itself.

Towards a Cognitive Theory of Multimedia Assessment (CTMMA)

NARCIS (Netherlands)

Kirschner, Paul A.; Park, Babette; Malone, Sarah; Jarodzka, Halszka

2017-01-01

Much is known about assessment in all its forms and the corpus of theory and knowledge is growing daily. In a similar vein, the use of multimedia for learning also has a sound basis in research and theory, such as the Cognitive Load Theory (CLT; Sweller, Van Merriënboer, & Paas, 1998), human

Psychoacoustic entropy theory and its implications for performance practice

Science.gov (United States)

Strohman, Gregory J.

This dissertation attempts to motivate, derive and imply potential uses for a generalized perceptual theory of musical harmony called psychoacoustic entropy theory. This theory treats the human auditory system as a physical system which takes acoustic measurements. As a result, the human auditory system is subject to all the appropriate uncertainties and limitations of other physical measurement systems. This is the theoretic basis for defining psychoacoustic entropy. Psychoacoustic entropy is a numerical quantity which indexes the degree to which the human auditory system perceives instantaneous disorder within a sound pressure wave. Chapter one explains the importance of harmonic analysis as a tool for performance practice. It also outlines the critical limitations for many of the most influential historical approaches to modeling harmonic stability, particularly when compared to available scientific research in psychoacoustics. Rather than analyze a musical excerpt, psychoacoustic entropy is calculated directly from sound pressure waves themselves. This frames psychoacoustic entropy theory in the most general possible terms as a theory of musical harmony, enabling it to be invoked for any perceivable sound. Chapter two provides and examines many widely accepted mathematical models of the acoustics and psychoacoustics of these sound pressure waves. Chapter three introduces entropy as a precise way of measuring perceived uncertainty in sound pressure waves. Entropy is used, in combination with the acoustic and psychoacoustic models introduced in chapter two, to motivate the mathematical formulation of psychoacoustic entropy theory. Chapter four shows how to use psychoacoustic entropy theory to analyze the certain types of musical harmonies, while chapter five applies the analytical tools developed in chapter four to two short musical excerpts to influence their interpretation. Almost every form of harmonic analysis invokes some degree of mathematical reasoning

The Effect of Religion on Ethnic Tolerance in Malaysia: The Application of Rational Choice Theory (RCT) and the Theory of Planned Behaviour (TPB)

Science.gov (United States)

Idris, Fazilah; Abdullah, Mohd Richard Neles; Ahmad, Abdul Razak; Mansor, Ahmad Zamri

2016-01-01

There has been little research done on explaining the ethnic tolerance behavior from the perspective of sociological theories. The authors chose rational choice theory and the theory of planned behavior as they are widely used in explaining the human social behaviour. In this article, the theories are used to explain the effects of religion on…

Can the Theory of Motivation Explain Migration Decisions?

OpenAIRE

Natálie Reichlová

2005-01-01

According to Abraham Maslow's motivational theory, human action is motivated by five groups of human needs. The model introduced in this paper exploits Maslow's theory to explain migration flows between regions. In the model, movement from one place to another influences migrant's utility through three various ways. First, through change in wage caused by different wage levels in each location. Second, through changes in utility connected with individuals safety needs and finally, through dis...

Human and Inhuman Capital, and Schooling

Directory of Open Access Journals (Sweden)

Primož Krašovec

2014-06-01

Full Text Available Theories of human capital are becoming an increasingly common reference in both newer pedagogical theories as well as political documents, outlining the plans for reforms of science and education. As a part of broader ideology of knowledge society, human capital theories represent ideological legitimation of neoliberal trends in science and education policies. Increased investment in human capital on both social and individual level is supposed to increase the competitiveness of the economy as a whole as well as employability and welfare of individuals. In the first part of the article, we sketch the intellectual history and the socio-political context of the development of theories of human capital. Second part is dedicated to a critique of characteristically neoliberal equalization of labor with capital and of a theory, according to which investment in human capital brings profits to individual workers. In the third part, we outline a general socio-historical dynamics of the development of high-tech capitalism and show that “investments in human capital” and economic innovations do not bring about increased social welfare. In the fourth, final part, we analyze in detail how current educational reforms impact the learning process and working conditions at public universities.

MacIntyre's Moral Theory and Moral Relativism

OpenAIRE

Ali Abedi Renani

2017-01-01

In this paper, I seek to explain the similarity and disparity between MacIntyre’s moral theory and moral relativism. I will argue that MacIntyre’s moral theory can escape the charge of moral relativism because both his earlier social and his later metaphysical approaches appeal to some criteria, the human telos or universal human qualities respectively. The notion of telos is wider than the notion of function which is defined in social contexts. If there is a context-transcending notion of te...

Affordances in activity theory and cognitive systems engineering

DEFF Research Database (Denmark)

Albrechtsen, H.; Andersen, H.H.K.; Bødker, S.

2001-01-01

on design for low level interaction modalities. To incorporate the concept of affordances in the design of human computer interaction it is necessary to systematically unravel affordances that supporthuman action possibilities. Furthermore, it is a necessity that Gibson's theory of affordances...... is supplemented by careful analyses of other human modalities and activities than visual perception. Within HMI two well established perspectives on HMI,Activity Theory (AT) and Cognitive Systems Engineering (CSE), have discussed such analyses and design of action possibilities focusing on providing computer...... to cover deeper semantic and pragmatic aspects of the ecology of work, as compared with the previous applications of Gibson's theory in HMI....

Time Breath of Psychological Theories

DEFF Research Database (Denmark)

Tateo, Luca; Valsiner, Jaan

2015-01-01

Psychology as a self-aspiring, ambitious, developmental science faces the crucial limit of time—both theoretically and practically. The issue of time in constructing psychology’s theories is a major unresolved metatheoretical task. This raises several questions about generalization of knowledge...... of time—or fail to do that? How can they generalize with respect to time? The different conceptions of time often remain implicit, while shaping the concepts used in understanding psychological processes. Any preconception about time in human development will foster the generalizability of theory, as well......: which is the time length of breath of psychological theories? Which is the temporal dimension of psychological processes? In this article we discuss the role of different axiomatic assumptions about time in the construction of psychological theories. How could different theories include a concept...

Machine learning and complex-network for personalized and systems biomedicine

KAUST Repository

Cannistraci, Carlo Vittorio

2016-01-27

The talk will begin with an introduction on using machine learning to discover hidden information and unexpected patterns in large biomedical datasets. Then, recent results on the use of complex network theory in biomedicine and neuroscience will be discussed. In particular, metagenomics and metabolomics data, approaches for drug-target repositioning, functional/structural MR connectomes and gut-brain axis data will be presented. The conclusion will outline the novel and exciting perspectives offered by the translation of these methods from systems biology to systems medicine.

The Theory of Caritative Leadership Applied to Education

Science.gov (United States)

Näsman, Yvonne

2018-01-01

Within caring science, the concept of caring leadership is well established. The aim of this study is to introduce Bondas's theory of caritative leadership into education. The theory of caritative leadership is a theory of caring leadership with the 'caritas' thought of human love and mercy at its core. The article considers a hypothetical testing…

Activity theory as a potential framework for technology research in ...

African Journals Online (AJOL)

This article attempts to expand and elaborate Activity Theory as a theory for studying human computer interaction in South Africa. It first sketches ways in which. Russian activity theory arising out of the work of Vygotsky may expand understandings of learning before elaborating the theory in terms of Engestrom's

Toward a Unified Consciousness Theory

Science.gov (United States)

Johnson, Richard H.

1977-01-01

The beginning of a holistic theory that can treat paranormal phenomena as normal human development is presented. Implications for counseling, counselor education, and counselor supervision are discussed. (Author)

Extraction of human gait signatures: an inverse kinematic approach using Groebner basis theory applied to gait cycle analysis

Science.gov (United States)

Barki, Anum; Kendricks, Kimberly; Tuttle, Ronald F.; Bunker, David J.; Borel, Christoph C.

2013-05-01

This research highlights the results obtained from applying the method of inverse kinematics, using Groebner basis theory, to the human gait cycle to extract and identify lower extremity gait signatures. The increased threat from suicide bombers and the force protection issues of today have motivated a team at Air Force Institute of Technology (AFIT) to research pattern recognition in the human gait cycle. The purpose of this research is to identify gait signatures of human subjects and distinguish between subjects carrying a load to those subjects without a load. These signatures were investigated via a model of the lower extremities based on motion capture observations, in particular, foot placement and the joint angles for subjects affected by carrying extra load on the body. The human gait cycle was captured and analyzed using a developed toolkit consisting of an inverse kinematic motion model of the lower extremity and a graphical user interface. Hip, knee, and ankle angles were analyzed to identify gait angle variance and range of motion. Female subjects exhibited the most knee angle variance and produced a proportional correlation between knee flexion and load carriage.

Using actor-network theory to study an educational situation: an ...

African Journals Online (AJOL)

Actor-network theory allows a researcher to analyse a complex social setting involving both human and non-human actors. An actor network can be used to model a dynamic and complex set of relationships between these actors. This article describes actor-network theory and shows how it was applied to study and model ...

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

Science.gov (United States)

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

Ancestral trees for modeling stem cell lineages genetically rather than functionally: understanding mutation accumulation and distinguishing the restrictive cancer stem cell propagation theory and the unrestricted cell propagation theory of human tumorigenesis.

Science.gov (United States)

Shibata, Darryl K; Kern, Scott E

2008-01-01

Cancer stem cells either could be rare or common in tumors, constituting the major distinction between the two fundamentally opposed theoretical models of tumor progression: A newer and restrictive stem cell propagation model, in which the stem cells are a small and special minority of the tumor cells, and a standard older model, an unrestricted cell proliferation theory, in which many or most tumor cells are capable of indefinite generations of cell division. Stem cells of tumors are difficult to quantitate using functional assays, and the validity of the most common assays is seriously questioned. Nonetheless, stem cells are an essential component of any tumorigenesis model. Alternative approaches to studying tumor stem cells should be explored. Cell populations can be conceived of as having a genealogy, a relationship of cells to their ancestral lineage, from the zygote to the adult cells or neoplasms. Models using ancestral trees thus offer an anatomic and genetic means to "observe" stem cells independent of artificial conditions. Ancestral trees broaden our attention backward along a lineage, to the zygote stage, and thereby add insight into how the mutations of tumors accumulate. It is possible that a large fraction of mutations in a tumor originate from normal, endogenous, replication errors (nearly all being passenger mutations) occurring prior to the emergence of the first transformed cell. Trees can be constructed from experimental measurements - molecular clocks - of real human tissues and tumors. Detailed analysis of single-cell methylation patterns, heritable yet slightly plastic, now can provide this information in the necessary depth. Trees based on observations of molecular clocks may help us to distinguish between competing theories regarding the proliferative properties among cells of actual human tumors, to observe subtle and difficult phenomena such as the extinction of stem lineages, and to address the origins and rates of mutations in various

Musical rhythm and affect. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

Science.gov (United States)

Witek, Maria A. G.; Kringelbach, Morten L.; Vuust, Peter

2015-06-01

The Quartet Theory of Human Emotion (QT) proposed by Koelsch et al. [1] adds to existing affective models, e.g. by directing more attention to emotional contagion, attachment-related and non-goal-directed emotions. Such an approach seems particularly appropriate to modelling musical emotions, and music is indeed a recurring example in the text, used to illustrate the distinct characteristics of the affect systems that are at the centre of the theory. Yet, it would seem important for any theory of emotion to account for basic functions such as prediction and anticipation, which are only briefly mentioned. Here we propose that QT, specifically its focus on emotional contagion, attachment-related and non-goal directed emotions, might help generate new ideas about a largely neglected source of emotion - rhythm - a musical property that relies fundamentally on the mechanism of prediction.

Contours of New Economic Theory

Directory of Open Access Journals (Sweden)

Garry Jacobs

2015-05-01

Full Text Available The need for a paradigm change in economic thought has been well established, but the contours and fundamental characteristics of a new paradigm in economic theory are yet to be worked out. This article views this transition as an inevitable expression of the maturation of the social sciences into an integrated trans-disciplinary science of society founded on common underlying principles, premises and processes. It calls for evolution of human-centered, value-based economic theory whose objective is to maximize human economic security, welfare and well-being rather than economic growth. It emphasizes the determinative role of fundamental creative social processes expressing in all fields of human endeavor. It argues for extending the boundaries of economics to encompass the entire gamut of political, legal, social, psychological, intellectual, organizational and ecological factors that directly and indirectly contribute to economic security, welfare and well-being. The article concludes with a list of anticipated practical implications.

论王安石“善恶由习”人性论的理论渊源及其内容%On the Theoretical Origins and Contents of Wang Anshi＇s Theory of Human Nature on the Good and Evil Emerged from the Habit and Custom

Institute of Scientific and Technical Information of China (English)

欧阳辉纯

2012-01-01

Traditional ethical thinking theory of human nature provided theoretical basis for Wang Anshi＇ s. The theory of human nature in traditional ethical thinking history is mainly as follows, that is, the theory advanced by Mencius that human nature is good from birth, the theory put forward by Xunzi that human nature is evil from birth, the theory put forward by Sh- ishuo that human nature is both good and evil from birth, the Sanpin theory advanced by Dong Zhongshu, the theory put for-ward by Yangxiong that human nature is mixed goodness and evilness, and the Sanpin theory of disposition advanced by Hanyu. Wang Anshi＇s theory of human nature on the good and evil emerged from the habit and custom originates from critical-ly drawing on the results of previous theory of human nature. It is to the traditional theory of human nature to inject new mean-ing, to open up new realm, and thus it has an important position in traditional ethical thinking history in China.%传统人性论是王安石人性论形成的理论来源。传统伦理思想史上的人性论主要有孟子的性善论、告子的性无善无恶论、苟子的性恶论、世硕的性有善有恶论、董仲舒的性三品论、扬雄的性善恶混论和韩愈的性情三品说。王安石批判地吸收了前人的人性论成果，形成了他的“善恶由习”的人性论。他的人性论给传统人性论注入了新的内涵，开拓了新的境界，因而在中国伦理思想史上具有重要的地位。

Humans, Intentionality, Experience And Tools For Learning: Some Contributions From Post-cognitive Theories To The Use Of Technology In Physics Education

Science.gov (United States)

Bernhard, Jonte

2007-11-01

Human cognition cannot be properly understood if we do not take the use of tools into account. The English word cognition stems from the Latin "cognoscere," meaning "to become acquainted with" or "to come to know." Following the original Latin meaning we should not only study "what happens in the head" if we want to study cognition. Experientially based perspectives, such as pragmatism, phenomenology, phenomenography, and activity theory, stress that we should study person-world relationships. Technologies actively shape the character of human-world relationships. An emergent understanding in modern cognitive research is the co-evolution of the human brain and human use of tools and the active character of perception. Thus, I argue that we must analyze the role of technologies in physics education in order to realize their full potential as tools for learning, and I will provide selected examples from physics learning environments to support this assertion.

Game Theory An Introduction

CERN Document Server

Barron, E N

2008-01-01

A fundamental introduction to modern game theory from a mathematical viewpoint. Game theory arises in almost every fact of human and inhuman interaction since oftentimes during these communications objectives are opposed or cooperation is viewed as an option. From economics and finance to biology and computer science, researchers and practitioners are often put in complex decision-making scenarios, whether they are interacting with each other or working with evolving technology and artificial intelligence. Acknowledging the role of mathematics in making logical and advantageous decisions, Game

An Elementary Introduction to Statistical Learning Theory

CERN Document Server

Kulkarni, Sanjeev

2011-01-01

A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these areas at a level and in a way that is not often found in other books on the topic, the authors present the basic theory behind contemporary machine learning and

Applying Social Capital Theory and the Technology Acceptance ...

African Journals Online (AJOL)

Applying Social Capital Theory and the Technology Acceptance Model in information and knowledge sharing research. ... Inkanyiso: Journal of Humanities and Social Sciences ... The paper explains the components, relevance and practical applicability of the two theories to information and knowledge sharing research.

Animal Sociology and a Natural Economy of the Body Politic, Part II: The Past Is the Contested Zone: Human Nature and Theories of Production and Reproduction in Primate Behavior Studies.

Science.gov (United States)

Haraway, Donna

1978-01-01

Theories of animal and human society based on sex and reproduction have been powerful in legitimating beliefs in the natural necessity of aggression, competition, and hierarchy. Feminists attempting to answer this bias are caught in a political-scientific struggle to formulate and articulate adequate biosocial theories. (Author/KR)

Human Development XII: A Theory for the Structure and Function of the Human Brain

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Søren Ventegodt

2008-01-01

Full Text Available The human brain is probably the most complicated single structure in the biological universe. The cerebral cortex that is traditionally connected with consciousness is extremely complex. The brain contains approximately 1,000,000 km of nerve fibers, indicating its enormous complexity and which makes it difficult for scientists to reveal the function of the brain. In this paper, we propose a new model for brain functions, i.e., information-guided self-organization of neural patterns, where information is provided from the abstract wholeness of the biophysical system of an organism (often called the true self, or the “soul””. We present a number of arguments in favor of this model that provide self-conscious control over the thought process or cognition. Our arguments arise from analyzing experimental data from different research fields: histology, anatomy, electroencephalography (EEG, cerebral blood flow, neuropsychology, evolutionary studies, and mathematics. We criticize the popular network theories as the consequence of a simplistic, mechanical interpretation of reality (philosophical materialism applied to the brain. We demonstrate how viewing brain functions as information-guided self-organization of neural patterns can explain the structure of conscious mentation; we seem to have a dual hierarchical representation in the cerebral cortex: one for sensation-perception and one for will-action. The model explains many of our unique mental abilities to think, memorize, associate, discriminate, and make abstractions. The presented model of the conscious brain also seems to be able to explain the function of the simpler brains, such as those of insects and hydra.

Evolutionary considerations on complex emotions and music-induced emotions. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

Science.gov (United States)

Gingras, Bruno; Marin, Manuela M.

2015-06-01

Recent efforts to uncover the neural underpinnings of emotional experiences have provided a foundation for novel neurophysiological theories of emotions, adding to the existing body of psychophysiological, motivational, and evolutionary theories. Besides explicitly modeling human-specific emotions and considering the interactions between emotions and language, Koelsch et al.'s original contribution to this challenging endeavor is to identify four brain areas as distinct "affect systems" which differ in terms of emotional qualia and evolutionary pathways [1]. Here, we comment on some features of this promising Quartet Theory of Emotions, focusing particularly on evolutionary and biological aspects related to the four affect systems and their relation to prevailing emotion theories, as well as on the role of music-induced emotions.

Econophysics: from Game Theory and Information Theory to Quantum Mechanics

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Jimenez, Edward; Moya, Douglas

2005-03-01

Rationality is the universal invariant among human behavior, universe physical laws and ordered and complex biological systems. Econophysics isboth the use of physical concepts in Finance and Economics, and the use of Information Economics in Physics. In special, we will show that it is possible to obtain the Quantum Mechanics principles using Information and Game Theory.

Management applications of discontinuity theory

Science.gov (United States)

Angeler, David G.; Allen, Craig R.; Barichievy, Chris; Eason, Tarsha; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance H.; Knutson, Melinda; Nash, Kirsty L.; Nelson, R. John; Nystrom, Magnus; Spanbauer, Trisha; Stow, Craig A.; Sundstrom, Shana M.

2015-01-01

Human impacts on the environment are multifaceted and can occur across distinct spatiotemporal scales. Ecological responses to environmental change are therefore difficult to predict, and entail large degrees of uncertainty. Such uncertainty requires robust tools for management to sustain ecosystem goods and services and maintain resilient ecosystems.We propose an approach based on discontinuity theory that accounts for patterns and processes at distinct spatial and temporal scales, an inherent property of ecological systems. Discontinuity theory has not been applied in natural resource management and could therefore improve ecosystem management because it explicitly accounts for ecological complexity.Synthesis and applications. We highlight the application of discontinuity approaches for meeting management goals. Specifically, discontinuity approaches have significant potential to measure and thus understand the resilience of ecosystems, to objectively identify critical scales of space and time in ecological systems at which human impact might be most severe, to provide warning indicators of regime change, to help predict and understand biological invasions and extinctions and to focus monitoring efforts. Discontinuity theory can complement current approaches, providing a broader paradigm for ecological management and conservation.

Practical theories

DEFF Research Database (Denmark)

Jensen, Klaus Bruhn

2016-01-01

This article revisits the place of normative and other practical issues in the wider conceptual architecture of communication theory, building on the tradition of philosophical pragmatism. The article first characterizes everyday concepts of communication as the accumulated outcome of natural...... evolution and history: practical resources for human existence and social coexistence. Such practical concepts have served as the point of departure for diverse theoretical conceptions of what communication is. The second part of the article highlights the past neglect and current potential of normative...... communication theories that ask, in addition, what communication ought to be, and what it could be, taking the relationship between communication and justice as a case in point. The final section returns to empirical conceptualizations of different institutions, practices and discourses of communication...

Perceived Quality of Private Education and Fears of Stratification: Investigating the Propositions of Human Capital Theory by Exploring the Case of Colombia

Science.gov (United States)

Nel Páez, Pedro; Teelken, Christine

2016-01-01

The purpose of this paper is to discuss the recent developments in the higher education system of Colombia in order to illustrate how these encourage stratification between (types of) universities and their students. We do so by discussing propositions generated by human capital theory and apply them to the experiences of students and graduates…

Classical logic and logicism in human thought

OpenAIRE

Elqayam, Shira

2012-01-01

This chapter explores the role of classical logic as a theory of human reasoning. I distinguish between classical logic as a normative, computational and algorithmic system, and review its role is theories of human reasoning since the 1960s. The thesis I defend is that psychological theories have been moving further and further away from classical logic on all three levels. I examine some prominent example of logicist theories, which incorporate logic in their psychological account, includin...

A nursing theory-guided framework for genetic and epigenetic research.

Science.gov (United States)

Maki, Katherine A; DeVon, Holli A

2018-04-01

The notion that genetics, through natural selection, determines innate traits has led to much debate and divergence of thought on the impact of innate traits on the human phenotype. The purpose of this synthesis was to examine how innate theory informs genetic research and how understanding innate theory through the lens of Martha Rogers' theory of unitary human beings can offer a contemporary view of how innate traits can inform epigenetic and genetic research. We also propose a new conceptual model for genetic and epigenetic research. The philosophical, theoretical, and research literatures were examined for this synthesis. We have merged philosophical and conceptual phenomena from innate theory with the theory of unitary beings into the University of Illinois at Chicago model for genetic and epigenetic research. Innate traits are the cornerstone of the framework but may be modified epigenetically by biological, physiological, psychological, and social determinants as they are transcribed. These modifiers serve as important links between the concept of innate traits and epigenetic modifications, and, like the theory of unitary human beings, the process is understood in the context of individual and environmental interaction that has the potential to evolve as the determinants change. © 2018 John Wiley & Sons Ltd.

Ethical principles and theories.

Science.gov (United States)

Schultz, R C

1993-01-01

Ethical theory about what is right and good in human conduct lies behind the issues practitioners face and the codes they turn to for guidance; it also provides guidance for actions, practices, and policies. Principles of obligation, such as egoism, utilitarianism, and deontology, offer general answers to the question, "Which acts/practices are morally right?" A re-emerging alternative to using such principles to assess individual conduct is to center normative theory on personal virtues. For structuring society's institutions, principles of social justice offer alternative answers to the question, "How should social benefits and burdens be distributed?" But human concerns about right and good call for more than just theoretical responses. Some critics (eg, the postmodernists and the feminists) charge that normative ethical theorizing is a misguided enterprise. However, that charge should be taken as a caution and not as a refutation of normative ethical theorizing.

Zone of Proximal Development (ZPD) as an Emergent System: A Dynamic Systems Theory Perspective.

Science.gov (United States)

Karimi-Aghdam, Saeed

2017-03-01

This paper sets out to present a novel construal of one of the notions of Vygotskian cultural-historical theory viz., zone of proximal development (ZPD) drawing upon dynamic systems theory. The principal thesis maintains that ZDP is an emergent and dynamic system which is engendered by a dialectical concatenation of psychogenesic and sociogenesic facets of human development over time. It is reasoned that Vygotskian cultural-historical theory of human development, by invoking dialectical logic, has transcended Cartesian substance dualism and in turn has proffered a monistic and process-anchored ontology for emerging becoming of human consciousness. Likewise, it is contended that dynamic systems theory, having assumed fluent flux of reality with a capital R as its ontological axiom, entails a consilience of cognitive and contextual conceptual schemes to describe, explain, and optimize human development. The paper concludes by drawing some interpretive conclusions in regard to ZPD from dynamic systems theory perspective.

Human Rights in National Administrative Law

DEFF Research Database (Denmark)

Næsborg-Andersen, Ayo

rights law is visible in the case-law of institutions performing reviews of Danish administrative decisions. The book consists of three parts. The first part contains the introduction, research question, methodological considerations and delimitations. The second part is an in-depth look at the theory...... developed using the theory of legal capability and communication theories. Discussing new ways of analysing the application of human rights, this book is relevant for scholars and professionals primarily working with human rights law, but also administrative law, both nationally and internationally.......Human rights are increasingly debated in the public sphere, yet discussions of human rights law are traditionally all but invisible in the discussions on national administrative law. This is at least the case in Denmark. This book sets out to analyse if, and in what way, the application of human...

Prospects of a mathematical theory of human behavior in complex man-machine systems tasks. [time sharing computer analogy of automobile driving

Science.gov (United States)

Johannsen, G.; Rouse, W. B.

1978-01-01

A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued.

Theoretical and Methodological Approaches to Understanding Human Migration Patterns and their Utility in Forensic Human Identification Cases

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Anastasia Holobinko

2012-06-01

Full Text Available Human migration patterns are of interest to scientists representing many fields. Theories have been posited to explain modern human evolutionary expansion, the diversity of human culture, and the motivational factors underlying an individual or group decision to migrate. Although the research question and subsequent approach may vary between disciplines, one thread is ubiquitous throughout most migration studies: why do humans migrate and what is the result of such an event? While the determination of individual attributes such as age, sex, and ancestry is often integral to migration studies, the positive identification of human remains is usually irrelevant. However, the positive identification of a deceased is paramount to a forensic investigation in which human remains have been recovered and must be identified. What role, if any, might the study of human movement patterns play in the interpretation of evidence associated with unidentified human remains? Due to increasing global mobility in the world's populations, it is not inconceivable that an individual might die far away from his or her home. If positive identification cannot immediately be made, investigators may consider various theories as to how or why a deceased ended up in a particular geographic location. While scientific evidence influences the direction of forensic investigations, qualitative evaluation can be an important component of evidence interpretation. This review explores several modern human migration theories and the methodologies utilized to identify evidence of human migratory movement before addressing the practical application of migration theory to forensic cases requiring the identification of human remains.

Behavioral data requirements for translating cognitive theories into computer software algorithms

International Nuclear Information System (INIS)

Meister, D.

1992-01-01

This paper reviews the characteristics of cognitive theories and their links to behavioral science and advanced intelligent systems. Cognitive theories model human cognition, perception, and communication. They suggest the human functions the system should have, serve as a philosophical basis for system development, and provide abstract design guidelines. The underlying assumption behind this paper is that if the cognitive theories are to have any value at all, they must be translated into usable systems. A process for testing a cognitive theory in terms of conceptual criteria, behavioral predictions and tests, and software development and tests, is suggested. Criteria for measuring the problem solving success of the advanced system are described. A theory of the system as an intelligent problem solver is presented. (author)

The Psychology of Career Theory--A New Perspective?

Science.gov (United States)

Woodd, Maureen

2000-01-01

New perspectives on human behavior have invalidated some assumptions of career theories such as personality type, career stages, and life-cycle models. Other theories, such as Driver's Objective Career Patterns, Schein's Temporal Development Model, and Nicholson's Transition Cycle, are compatible with current psychological understanding. (SK)

J. Piaget's theory of intelligence: operational aspect

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Xenia Naidenova

2001-08-01

Full Text Available The Piaget's theory of intelligence is considered from the point of view of genesis and gradual development of human thinking operations. Attention is given to operational aspects of cognitive structures and knowledge. The significance of the Piaget's theory of intelligence is revealed for modeling conceptual reasoning in the framework of artificial intelligence.

Quantum Field Theory

CERN Document Server

Zeidler, Eberhard

This is the first volume of a modern introduction to quantum field theory which addresses both mathematicians and physicists ranging from advanced undergraduate students to professional scientists. The book tries to bridge the existing gap between the different languages used by mathematicians and physicists. For students of mathematics it is shown that detailed knowledge of the physical background helps to motivate the mathematical subjects and to discover interesting interrelationships between quite different mathematical topics. For students of physics, fairly advanced mathematics is presented, which is beyond the usual curriculum in physics. It is the author's goal to present the state of the art of realizing Einstein's dream of a unified theory for the four fundamental forces in the universe (gravitational, electromagnetic, strong, and weak interaction). From the reviews: "… Quantum field theory is one of the great intellectual edifices in the history of human thought. … This volume differs from othe...

Livability theory

OpenAIRE

Veenhoven, Ruut

2014-01-01

markdownabstract__Abstract__ Assumptions Livability theory involves the following six key assumptions: 1. Like all animals, humans have innate needs, such as for food, safety, and companionship. 2. Gratification of needs manifests in hedonic experience. 3. Hedonic experience determines how much we like the life we live (happiness). Hence, happiness depends on need gratification. 4.Need gratification depends on both external living conditions and inner abilities to use these. Hence, bad living...

Correlations between Theories of Human Nature and Politics: A Search for a Relationship in the Work of Dewey and Rawls

Science.gov (United States)

1988-04-08

to fathom assertion, but at lest two qualifications should be made. First, we must not confuse the idea with egoism . Even though the parties are...14Aristotle Nicomachean Ethics 5. 3. 1131a25. 15Rawls, Theory of Justice, p. 156. 16Actually, we might argue for a three part division in Rawls: noumenal...nature/nurture portion of the self. pij BIBLIOGRAPHY OF WORKS CITED Aristotle. Nicomachean Ethics . Dewey, John. Human Nature and Conduct: An

Quality of Life Theory III. Maslow Revisited