Lying and Neuroscience

2018 ◽  
pp. 455-468
Author(s):  
Giorgio Ganis
Keyword(s):  
Cognitive Neuroscience ◽  
Deception Detection ◽  
General Purpose ◽  
Neural Activation ◽  
Potential Applications ◽  
Key Features ◽  
Theoretical Question

This chapter provides an overview of the literature on the cognitive neuroscience of deception and deception-detection. First, the two main classes of deception paradigms are briefly introduced and some of their key features are discussed. Next, key results of electrophysiological and neuroimaging studies are summarized and the main findings reviewed, in terms of both theoretical implications and potential applications. The key theoretical question about whether the patterns of neural activation found in these neuroimaging studies reflect deception-specific processes or, conversely, general-purpose processes, is discussed in detail within the context of reverse inferences in cognitive neuroscience.

scholarly journals CAR-T cells leave the comfort zone: current and future applications beyond cancer

2020 ◽  
Author(s):  
Mariana Torres Mazzi ◽  
Karina Lôbo Hajdu ◽  
Priscila Rafaela Ribeiro ◽  
Martín Hernán Bonamino
Keyword(s):  
T Cells ◽  
Cardiac Fibrosis ◽  
Tumor Therapy ◽  
General Purpose ◽  
Great Success ◽  
T Cell Therapy ◽  
Car T Cells ◽  
Car T ◽  
Potential Applications ◽  
Membrane Antigens

Abstract Chimeric antigen receptor (CAR)-T cell therapy represents a breakthrough in the immunotherapy field and has achieved great success following its approval in 2017 for the treatment of B cell malignancies. While CAR-T cells are mostly applied as anti-tumor therapy in the present, their initial concept was aimed at a more general purpose of targeting membrane antigens, thus translating in many potential applications. Since then, several studies have assessed the use of CAR-T cells towards non-malignant pathologies such as autoimmune diseases, infectious diseases and, more recently, cardiac fibrosis and cellular senescence. In this review, we present the main findings and implications of CAR-based therapies for non-malignant conditions.

scholarly journals Cognition, Concurrency Theory and Reverberations in the Brain: in Search of a Calculus of Communicating (Recurrent) Neural Systems

10.29007/94w5 ◽  
2018 ◽  
Author(s):  
Howard Bowman ◽  
Li Su
Keyword(s):  
Cognitive Neuroscience ◽  
Learning Algorithm ◽  
Severe Form ◽  
Neural Systems ◽  
System Description ◽  
Structural Decomposition ◽  
Neural Network Learning ◽  
Concurrency Theory ◽  
Potential Applications ◽  
The Brain

We consider whether techniques from concurrency theory can be applied in the area of Cognitive Neuroscience. We focus on two potential applications. The first of these explores structural decomposition, which is effectively assumed by the localisation of function metaphor that so dominates current Cognitive Neuroscience. We take concurrency theory methods, especially Process Calculi, as canonical illustrations of system description notations that support structural decomposition and, in particular, encapsulation of behaviour. We argue that carrying these behavioural and notational properties over to the Cognitive Neuroscience setting is difficult, since neural networks (the modelling method of choice) are not naturally encapsulable. Our second application presents work on verifying stability properties of neural network learning algorithms using model checking. We thereby present evidence that a particular learning algorithm, the Generalised Recirculation algorithm, exhibits an especially severe form of instability, whereby it forgets what it has learnt, while continuing to be trained on the same pattern set.

scholarly journals Pyrosequencing Sheds Light on DNA Sequencing

2001 ◽  
Vol 11 (1) ◽  
pp. 3-11
Author(s):  
Mostafa Ronaghi
Keyword(s):  
Dna Sequencing ◽  
Gel Electrophoresis ◽  
Chain Termination ◽  
Enzyme Properties ◽  
Sequence Determination ◽  
Detailed Characterization ◽  
Potential Applications ◽  
Key Features ◽  
Pyrosequencing Technology

DNA sequencing is one of the most important platforms for the study of biological systems today. Sequence determination is most commonly performed using dideoxy chain termination technology. Recently, pyrosequencing has emerged as a new sequencing methodology. This technique is a widely applicable, alternative technology for the detailed characterization of nucleic acids. Pyrosequencing has the potential advantages of accuracy, flexibility, parallel processing, and can be easily automated. Furthermore, the technique dispenses with the need for labeled primers, labeled nucleotides, and gel-electrophoresis. This article considers key features regarding different aspects of pyrosequencing technology, including the general principles, enzyme properties, sequencing modes, instrumentation, and potential applications.

Estimating the international burden of sport-related death: a review of data sources

2018 ◽  
Vol 25 (2) ◽  
pp. 83-89 ◽  
Author(s):  
Kristen L Kucera ◽  
Lauren V Fortington ◽  
Catherine S Wolff ◽  
Stephen W Marshall ◽  
Caroline F Finch
Keyword(s):  
International Comparisons ◽  
Sports Injury ◽  
General Purpose ◽  
Data Sources ◽  
International Organisations ◽  
Related Activity ◽  
Activity Data ◽  
Case Identification ◽  
International Data ◽  
Key Features

IntroductionDespite detailed recommendations for sports injury data capture provided since the mid-1990s, international data collection efforts for sport-related death remains limited in scope. The purpose of this paper was to review the data sources available for studying sport-related death and describe their key features, coverage, accessibility and strengths and limitations.MethodsThe outcomes of interest for this review was death occurring as a result of participation in organised sport-related activity. Data sources used to enumerate death in sport were identified, drawing from the authors’ knowledge/experience and review of key references from international organisations. The general purpose, case identification, structure, strengths and limitations of each source in relation to collection of data for sport-related death were summarised, drawing on examples from the international published literature to illustrate this application.ResultsSeven types of resources were identified for capturing deaths in sport. Data sources varied considerably in their ability to identify: participant status, sport relatedness of the death, types of sport-related deaths they capture, level of detail provided about the circumstances and medical care received. The most detailed sources were those that were dedicated to sports surveillance. Sport relatedness and type of sport may not be reliably captured by systems not dedicated to sports injury surveillance. Only one source permitted international comparisons and was limited to one sport (soccer).ConclusionData on sport-related death are currently collected across a wide variety of data sources. This review highlights the need for robust, comprehensive approaches with standardised methodologies enabling linkage between sources and international comparisons.

Using linguistically defined specific details to detect deception across domains

2019 ◽  
Vol 26 (3) ◽  
pp. 349-373
Author(s):  
Nikolai Vogler ◽  
Lisa Pearl
Keyword(s):  
Classification Accuracy ◽  
Deception Detection ◽  
General Purpose ◽  
Training Data ◽  
Data Sets ◽  
Potential Utility ◽  
Job Interview ◽  
Specific Detail ◽  
Cross Domain ◽  
Content Domain

AbstractCurrent automatic deception detection approaches tend to rely on cues that are based either on specific lexical items or on linguistically abstract features that are not necessarily motivated by the psychology of deception. Notably, while approaches relying on such features can do well when the content domain is similar for training and testing, they suffer when content changes occur. We investigate new linguistically defined features that aim to capture specific details, a psychologically motivated aspect of truthful versus deceptive language that may be diagnostic across content domains. To ascertain the potential utility of these features, we evaluate them on data sets representing a broad sample of deceptive language, including hotel reviews, opinions about emotionally charged topics, and answers to job interview questions. We additionally evaluate these features as part of a deception detection classifier. We find that these linguistically defined specific detail features are most useful for cross-domain deception detection when the training data differ significantly in content from the test data, and particularly benefit classification accuracy on deceptive documents. We discuss implications of our results for general-purpose approaches to deception detection.

ChemML: A Machine Learning and Informatics Program Package for the Analysis, Mining, and Modeling of Chemical and Materials Data

2019 ◽  
Author(s):  
Mojtaba Haghighatlari ◽  
Gaurav Vishwakarma ◽  
Doaa Altarawy ◽  
Ramachandran Subramanian ◽  
Bhargava Urala Kota ◽  
...  
Keyword(s):  
Machine Learning ◽  
In Silico ◽  
Data Science ◽  
General Purpose ◽  
Data Driven ◽  
Research Paradigm ◽  
User Friendliness ◽  
Methodological Innovation ◽  
Software Ecosystem ◽  
Key Features

<div><i>ChemML</i> is an open machine learning and informatics program suite that is designed to support and advance the data-driven research paradigm that is currently emerging in the chemical and materials domain. <i>ChemML</i> allows its users to perform various data science tasks and execute machine learning workflows that are adapted specifically for the chemical and materials context. Key features are automation, general-purpose utility, versatility, and user-friendliness in order to make the application of modern data science a viable and widely accessible proposition in the broader chemistry and materials community. <i>ChemML</i> is also designed to facilitate methodological innovation, and it is one of the cornerstones of the software ecosystem for data-driven <i>in silico</i> research outlined in our recent publication<sup>1</sup>.</div>

scholarly journals A dynamic model of the body gas stores for carbon dioxide, oxygen and inert gases that incorporates circulatory transport delays to and from the lung.

2021 ◽  
Author(s):  
Snapper Richard Myran Magor-Elliott ◽  
Christopher J. Fullerton ◽  
Graham Richmond ◽  
Grant A.D. Ritchie ◽  
Peter A. Robbins
Keyword(s):  
General Purpose ◽  
The Body ◽  
Inert Gases ◽  
Published Data ◽  
Model Predictions ◽  
Pulmonary Artery Catheters ◽  
Potential Applications ◽  
Respiratory Measurement ◽  
Rapid Transients ◽  
Arteries And Veins

Many models of the body's gas stores have been generated for specific purposes. Here, we seek to produce a more general purpose model that: i) is relevant for both respiratory (CO2 and O2) and inert gases; ii) is based firmly on anatomy and not arbitrary compartments; iii) can be scaled to individuals; and iv) incorporates arterial and venous circulatory delays as well as tissue volumes so that it can reflect rapid transients with greater precision. First, a 'standard man' of 11 compartments was produced, based on data compiled by the International Radiation Protection Commission. Each compartment was supplied via its own parallel circulation, the arterial and venous volumes of which were based on reported tissue blood volumes together with data from a detailed anatomical model for the large arteries and veins. A previously published model was used for the blood gas chemistry of CO2 and O2. It was not permissible ethically to insert pulmonary artery catheters into healthy volunteers for model validation. Therefore, validation was undertaken by comparing model predictions with previously published data and by comparing model predictions with experimental data for transients in gas exchange at the mouth following changes in alveolar gas composition. Overall, model transients were fastest for O2, intermediate for CO2 and slowest for N2. There was good agreement between model estimates and experimentally measured data. Potential applications of the model include estimation of closed-loop gain for the ventilatory chemoreflexes, and improving the precision associated with multibreath washout testing and respiratory measurement of cardiac output.

scholarly journals A synergy-based hand control is encoded in human motor cortical areas

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Andrea Leo ◽  
Giacomo Handjaras ◽  
Matteo Bianchi ◽  
Hamal Marino ◽  
Marco Gabiccini ◽  
...  
Keyword(s):  
Primary Motor Cortex ◽  
Brain Activity ◽  
Hand Movement ◽  
Movement Control ◽  
Neural Activation ◽  
Activation Patterns ◽  
Cortical Areas ◽  
Cortical Level ◽  
Potential Applications ◽  
Kinematic Synergies

How the human brain controls hand movements to carry out different tasks is still debated. The concept of synergy has been proposed to indicate functional modules that may simplify the control of hand postures by simultaneously recruiting sets of muscles and joints. However, whether and to what extent synergic hand postures are encoded as such at a cortical level remains unknown. Here, we combined kinematic, electromyography, and brain activity measures obtained by functional magnetic resonance imaging while subjects performed a variety of movements towards virtual objects. Hand postural information, encoded through kinematic synergies, were represented in cortical areas devoted to hand motor control and successfully discriminated individual grasping movements, significantly outperforming alternative somatotopic or muscle-based models. Importantly, hand postural synergies were predicted by neural activation patterns within primary motor cortex. These findings support a novel cortical organization for hand movement control and open potential applications for brain-computer interfaces and neuroprostheses.

scholarly journals Explicit Baker–Campbell–Hausdorff Expansions

Mathematics ◽  
2018 ◽  
Vol 6 (8) ◽  
pp. 135 ◽  
Author(s):  
Alexander Van-Brunt ◽  
Matt Visser
Keyword(s):  
Closed Form ◽  
General Purpose ◽  
Theoretical Physics ◽  
Closed Form Expression ◽  
Form Expression ◽  
Explicit Result ◽  
Special Cases ◽  
Potential Applications ◽  
Current Article ◽  
The Creation

The Baker–Campbell–Hausdorff (BCH) expansion is a general purpose tool of use in many branches of mathematics and theoretical physics. Only in some special cases can the expansion be evaluated in closed form. In an earlier article we demonstrated that whenever [X,Y]=uX+vY+cI, BCH expansion reduces to the tractable closed-form expression Z(X,Y)=ln(eXeY)=X+Y+f(u,v)[X,Y], where f(u,v)=f(v,u) is explicitly given by the the function f(u,v)=(u−v)eu+v−(ueu−vev)uv(eu−ev)=(u−v)−(ue−v−ve−u)uv(e−v−e−u). This result is much more general than those usually presented for either the Heisenberg commutator, [P,Q]=−iℏI, or the creation-destruction commutator, [a,a†]=I. In the current article, we provide an explicit and pedagogical exposition and further generalize and extend this result, primarily by relaxing the input assumptions. Under suitable conditions, to be discussed more fully in the text, and taking LAB=[A,B] as usual, we obtain the explicit result ln(eXeY)=X+Y+Ie−LX−e+LYI−e−LXLX+I−e+LYLY[X,Y]. We then indicate some potential applications.

ChemML: A Machine Learning and Informatics Program Package for the Analysis, Mining, and Modeling of Chemical and Materials Data

2019 ◽  
Author(s):  
Mojtaba Haghighatlari ◽  
Gaurav Vishwakarma ◽  
Doaa Altarawy ◽  
Ramachandran Subramanian ◽  
Bhargava Urala Kota ◽  
...  
Keyword(s):  
Machine Learning ◽  
In Silico ◽  
Data Science ◽  
General Purpose ◽  
Data Driven ◽  
Research Paradigm ◽  
User Friendliness ◽  
Methodological Innovation ◽  
Software Ecosystem ◽  
Key Features

<div><i>ChemML</i> is an open machine learning and informatics program suite that is designed to support and advance the data-driven research paradigm that is currently emerging in the chemical and materials domain. <i>ChemML</i> allows its users to perform various data science tasks and execute machine learning workflows that are adapted specifically for the chemical and materials context. Key features are automation, general-purpose utility, versatility, and user-friendliness in order to make the application of modern data science a viable and widely accessible proposition in the broader chemistry and materials community. <i>ChemML</i> is also designed to facilitate methodological innovation, and it is one of the cornerstones of the software ecosystem for data-driven <i>in silico</i> research outlined in our recent publication<sup>1</sup>.</div>

Sign in / Sign up

Export Citation Format

Share Document