The domain of organizational cognitive neuroscience:theoretical and empirical challenges

In this editorial, the authors respond to the 2011 article in the Journal of Management by Becker, Cropanzano, and Sanfey, titled “Organizational Neuroscience: Taking Organizational Theory Inside the Neural Black Box.” More specifically, the authors build on the ideas of Becker et al. first to clarify and extend their work and then to explore the critical philosophical issues involved in drawing inferences from neuroscientific research. They argue that these problems are yet to be solved and that organizational researchers who wish to incorporate neuroscientific advances into their work need to engage with them.

Synthetic, crystallographic, and computational study of copper(II) complexes of ethylenediaminetetracarboxylate ligands

Copper(II) complexes of hexadentate ethylenediaminetetracarboxylic acid type ligands Heda3p and Heddadp (Heda3p = ethylenediamine-N-acetic-N,N',N'-tri-3-propionic acid; H eddadp = ethylenediamine-N,N'-diacetic-N,N'-di-3- propionic acid) have been prepared. An octahedral trans(O) geometry (two propionate ligands coordinated in axial positions) has been established crystallographically for the Ba[Cu(eda3p)]·8HO compound, while Ba[Cu(eddadp)]·8HO is proposed to adopt a trans(O ) geometry (two axial acetates) on the basis of density functional theory calculations and comparisons of IR and UV-vis spectral data. Experimental and computed structural data correlating similar copper(II) chelate complexes have been used to better understand the isomerism and departure from regular octahedral geometry within the series. The in-plane O-Cu-N chelate angles show the smallest deviation from the ideal octahedral value of 90°, and hence the lowest strain, for the eddadp complex with two equatorial ß-propionate rings. A linear dependence between tetragonality and the number of five-membered rings has been established. A natural bonding orbital analysis of the series of complexes is also presented.

A multimodal perspective on the composition of cortical oscillations:frontiers in human neuroscience

An expanding corpus of research details the relationship between functional magnetic resonance imaging (fMRI) measures and neuronal network oscillations. Typically, integratedelectroencephalography(EEG) and fMRI,orparallel magnetoencephalography (MEG) and fMRI are used to draw inference about the consanguinity of BOLD and electrical measurements. However, there is a relative dearth of information about the relationship between E/MEG and the focal networks from which these signals emanate. Consequently, the genesis and composition of E/MEG oscillations requires further clarification. Here we aim to contribute to understanding through a series of parallel measurements of primary motor cortex (M1) oscillations, using human MEG and in-vitro rodent local field potentials. We compare spontaneous activity in the ~10Hz mu and 15-30Hz beta frequency ranges and compare MEG signals with independent and integrated layers III and V(LIII/LV) from in vitro recordings. We explore the mechanisms of oscillatory generation, using specific pharmacological modulation with the GABA-A alpha-1 subunit modulator zolpidem. Finally, to determine the contribution of cortico-cortical connectivity, we recorded in-vitro M1, during an incision to sever lateral connections between M1 and S1 cortices. We demonstrate that frequency distribution of MEG signals appear have closer statistically similarity with signals from integrated rather than independent LIII/LV laminae. GABAergic modulation in both modalities elicited comparable changes in the power of the beta band. Finally, cortico-cortical connectivity in sensorimotor cortex (SMC) appears to directly influence the power of the mu rhythm in LIII. These findings suggest that the MEG signal is an amalgam of outputs from LIII and LV, that multiple frequencies can arise from the same cortical area and that in vitro and MEG M1 oscillations are driven by comparable mechanisms. Finally, corticocortical connectivity is reflected in the power of the SMC mu rhythm. © 2013 Ronnqvist, Mcallister, Woodhall, Stanford and Hall.

Resource allocation in decentralised computational systems:an evolutionary market-based approach

We present a novel market-based method, inspired by retail markets, for resource allocation in fully decentralised systems where agents are self-interested. Our market mechanism requires no coordinating node or complex negotiation. The stability of outcome allocations, those at equilibrium, is analysed and compared for three buyer behaviour models. In order to capture the interaction between self-interested agents, we propose the use of competitive coevolution. Our approach is both highly scalable and may be tuned to achieve specified outcome resource allocations. We demonstrate the behaviour of our approach in simulation, where evolutionary market agents act on behalf of service providing nodes to adaptively price their resources over time, in response to market conditions. We show that this leads the system to the predicted outcome resource allocation. Furthermore, the system remains stable in the presence of small changes in price, when buyers' decision functions degrade gracefully. © 2009 The Author(s).

Toward an organizational cognitive neuroscience

The research strategy adopted in this article is to connect two different discourses and the ideas, methods, and outputs they contain—these being cognitive neuroscience and organization theory. The main contribution of the article is to present an agenda for the field of organizational cognitive neuroscience. We define what is meant by the term, outline its background, identify why it is important as a new research direction, and then conclude by drawing on Damasio's levels of life regulation as a framework to bind together existing organizational cognitive neuroscience. The article begins by setting the wider debate behind the emergence of organizational cognitive neuroscience by revisiting the nature–nurture debate and uses Pinker to demonstrate that the connection between mind and matter has not been resolved, that new directions are opening up to better understand human nature, and that organizational cognitive neuroscience is one fruitful path forward.

Replication-based inference algorithms for hard computational problems

Inference algorithms based on evolving interactions between replicated solutions are introduced and analyzed on a prototypical NP-hard problem: the capacity of the binary Ising perceptron. The efficiency of the algorithm is examined numerically against that of the parallel tempering algorithm, showing improved performance in terms of the results obtained, computing requirements and simplicity of implementation. © 2013 American Physical Society.

Investigation of a binding model for anti-cancer cyclohexadienones by computational chemistry and crystallography

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Computational mechanics analysis of the hidden conformational dynamics within a molecular trajectory

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The state of the art in organizational cognitive neuroscience:the therapeutic gap and possible implications for clinical practice

In the last decade, researchers in the social sciences have increasingly adopted neuroscientific techniques, with the consequent rise of research inspired by neuroscience in disciplines such as economics, marketing, decision sciences, and leadership. In 2007, we introduced the term organizational cognitive neuroscience (OCN), in an attempt to clearly demarcate research carried out in these many areas, and provide an overarching paradigm for research utilizing cognitive neuroscientific methods, theories, and concepts, within the organizational and business research fields. Here we will revisit and further refine the OCN paradigm, and define an approach where we feel the marriage of organizational theory and neuroscience will return even greater dividends in the future and that is within the field of clinical practice.

Modelling a biochemical reaction with computational fluid dynamics

Earlier investigations (Cartland Glover et al., 2004) into the use of computational fluid dynamics (CFD) for the modelling of gas-liquid and gas-liquid-solid flow allowed a simple biochemical reaction model to be implemented. A single plane mesh was used to represent the transport and reaction of molasses, the mould Aspergillus niger and citric acid in a bubble column with a height to diameter aspect ratio of 20:1. Two specific growth rates were used to examine the impact that biomass growth had on the local solids concentration and the effect this had on the local hydrodynamics of the bubble column.

Computational methods for traditional Chinese medicine:a survey

Traditional Chinese Medicine (TCM) has been actively researched through various approaches, including computational techniques. A review on basic elements of TCM is provided to illuminate various challenges and progresses in its study using computational methods. Information on various TCM formulations, in particular resources on databases of TCM formulations and their integration to Western medicine, are analyzed in several facets, such as TCM classifications, types of databases, and mining tools. Aspects of computational TCM diagnosis, namely inspection, auscultation, pulse analysis as well as TCM expert systems are reviewed in term of their benefits and drawbacks. Various approaches on exploring relationships among TCM components and finding genes/proteins relating to TCM symptom complex are also studied. This survey provides a summary on the advance of computational approaches for TCM and will be useful for future knowledge discovery in this area. © 2007 Elsevier Ireland Ltd. All rights reserved.

Intonation contour realisation for Standard Yorùbá text-to-speech synthesis:a fuzzy computational approach

This paper presents a novel intonation modelling approach and demonstrates its applicability using the Standard Yorùbá language. Our approach is motivated by the theory that abstract and realised forms of intonation and other dimensions of prosody should be modelled within a modular and unified framework. In our model, this framework is implemented using the Relational Tree (R-Tree) technique. The R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. Our R-Tree for an utterance is generated in two steps. First, the abstract structure of the waveform, called the Skeletal Tree (S-Tree), is generated using tone phonological rules for the target language. Second, the numerical values of the perceptually significant peaks and valleys on the S-Tree are computed using a fuzzy logic based model. The resulting points are then joined by applying interpolation techniques. The actual intonation contour is synthesised by Pitch Synchronous Overlap Technique (PSOLA) using the Praat software. We performed both quantitative and qualitative evaluations of our model. The preliminary results suggest that, although the model does not predict the numerical speech data as accurately as contemporary data-driven approaches, it produces synthetic speech with comparable intelligibility and naturalness. Furthermore, our model is easy to implement, interpret and adapt to other tone languages.

Neuromarketing and consumer neuroscience:contributions to neurology

Background: 'Neuromarketing' is a term that has often been used in the media in recent years. These public discussions have generally centered around potential ethical aspects and the public fear of negative consequences for society in general, and consumers in particular. However, positive contributions to the scientific discourse from developing a biological model that tries to explain context-situated human behavior such as consumption have often been neglected. We argue for a differentiated terminology, naming commercial applications of neuroscientific methods 'neuromarketing' and scientific ones 'consumer neuroscience'. While marketing scholars have eagerly integrated neuroscientific evidence into their theoretical framework, neurology has only recently started to draw its attention to the results of consumer neuroscience.Discussion: In this paper we address key research topics of consumer neuroscience that we think are of interest for neurologists; namely the reward system, trust and ethical issues. We argue that there are overlapping research topics in neurology and consumer neuroscience where both sides can profit from collaboration. Further, neurologists joining the public discussion of ethical issues surrounding neuromarketing and consumer neuroscience could contribute standards and experience gained in clinical research.Summary: We identify the following areas where consumer neuroscience could contribute to the field of neurology:. First, studies using game paradigms could help to gain further insights into the underlying pathophysiology of pathological gambling in Parkinson's disease, frontotemporal dementia, epilepsy, and Huntington's disease.Second, we identify compulsive buying as a common interest in neurology and consumer neuroscience. Paradigms commonly used in consumer neuroscience could be applied to patients suffering from Parkinson's disease and frontotemporal dementia to advance knowledge of this important behavioral symptom.Third, trust research in the medical context lacks empirical behavioral and neuroscientific evidence. Neurologists entering this field of research could profit from the extensive knowledge of the biological foundation of trust that scientists in economically-orientated neurosciences have gained.Fourth, neurologists could contribute significantly to the ethical debate about invasive methods in neuromarketing and consumer neuroscience. Further, neurologists should investigate biological and behavioral reactions of neurological patients to marketing and advertising measures, as they could show special consumer vulnerability and be subject to target marketing. © 2013 Javor et al.; licensee BioMed Central Ltd.