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V Sloutsky - One of the best experts on this subject based on the ideXlab platform.
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fMRI Evidence for a Three-Stage Model of Deductive Reasoning
Journal of cognitive neuroscience, 2006Co-Authors: Thomas Fangmeier, Christian C. Ruff, Markus Knauff, V SloutskyAbstract:Deductive reasoning is fundamental to science, human culture, and the solution of problems in daily life. It starts with premises and yields a logically necessary conclusion that is not explicit in the premises. Here we investigated the neurocognitive processes underlying logical thinking with event-related functional magnetic resonance imaging. We specifically focused on three temporally separable phases: (1) the premise processing phase, (2) the premise integration phase, and (3) the validation phase in which reasoners decide whether a conclusion logically follows from the premises. We found distinct patterns of cortical activity during these phases, with initial temporo-occipital activation shifting to the prefrontal cortex and then to the parietal cortex during the reasoning process. Activity in these latter regions was specific to reasoning, as it was significantly decreased during matched working memory problems with identical premises and equal working memory load.
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fmri evidence for a three stage Model of deductive reasoning
Conference Cognitive Science, 2005Co-Authors: Thomas Famgmeier, Markus Knauff, Christian C. Ruff, V SloutskyAbstract:FMRI-Evidence for a Three-Stage-Model of Deductive Reasoning Markus Knauff (markus.knauff@tuebingen.mpg.de) Max-Planck-Institute for Biological Cybernetics, 72076 Tubingen, Germany Centre for Cognitive Science, University Freiburg, 79098 Freiburg, Germany Thomas Famgmeier (thomas.fangmeier@cognition.iig.uni-freiburg.de) Centre for Cognitive Science, University Freiburg, 79098 Freiburg, Germany Christian C. Ruff (c.ruff@ucl.ac.uk) Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, United Kingdom Vladimir Sloutsky (Sloutsky.1@osu.edu) Center for Cognitive Science, The Ohio State University, Columbus, OH 43210, USA Abstract In an event-related fMRI study, we investigated the neuro- cognitive processes underlying deductive reasoning. We specifically focused on three temporally separable phases: (1) the premise processing phase, (2) the integration phase, and (3) the validation phase. We found distinct patterns of cortical activity during these phases, with initial temporo-occipital activation shifting to prefrontal and then parietal cortex during the reasoning process. Our findings demonstrate that human reasoning proceeds in separable phases, which are associated with distinct neuro-cognitive processes. Introduction Deductive reasoning starts with premises and yields a logically necessary conclusion that is not explicit in the premises. But what happens in the brain when we solve such deductive problems? Recent functional brain imaging studies have provided some first insights into the brain circuits underlying deductive reasoning. Reasoning with abstract premises seems to involve the right hemisphere, whereas reasoning with concrete material relies on processing in the left hemisphere (Goel, & Dolan, 2001; Goel, Buchel, Frith, & Dolan, 2000). During reasoning, portions of the parieto-occipital cortices are active, pointing to the role of visuo-spatial processes (Knauff, Mulack, Kassubek, Salih, & Greenlee, 2002; Knauff, Fangmeier, Ruff, & Johnson-Laird, 2003; Ruff, Knauff, Fangmeier, & Spreer, 2003). The more visual features are described in the reasoning problem, the more activity in occipital cortical areas can be found (Knauff, Fangmeier, Ruff, & Johnson- Laird, 2003). Moreover, reasoning-related activity in parietal areas correlates with visuo-spatial ability (Ruff, Knauff, Fangmeier, & Spreer, 2003). However, most of these studies have one pitfall in common. They presented the problems as sentences, either on the screen or via headphones. This means that reasoning- related brain activity may have been confounded by higher- level linguistic processing. In addition, many of these studies examined the brain activation during the whole reasoning process in a blocked fashion, and thus could not distinguish reasoning-related processes during different stages of problem processing. Only a few study so far compared the neuronal processes during the crucial conclusion sentence of the reasoning problem with the presentation of irrelevant control sentences (e.g. Goel, & Dolan, 2001). However, these control sentences clearly did not need to be processed as elaborately as the reasoning problems and the study did not provide any information what happens during premises processing. Thus, it is unclear whether reasoning is associated with distinct sub- processes not related to sentence processing, and how these processes may be differentially involved in different stages of reasoning. The aim of the present study was to disentangle the neuro- cognitive subprocesses underlying the different phases in the reasoning process, and at the same time to overcome the potential linguistic confound in the previous studies on the neuronal basis of deductive reasoning. We employed event- related functional magnetic resonance imaging with twelve participants, who solved (while in the scanner) 32 linear syllogisms (explanation below) with a spatial content. We decided to use problems with a spatial content, because spatial relations are easily understood by logically untrained participants. Since we aimed at distinguishing the pure reasoning process from the maintenance of information in working memory, in a second condition participants had to simply keep the premises of the identical problems in working memory (maintenance task) without making inferences (explanation below). Crucially, the premises and the conclusion of the inference problems were presented each as single display frames, by replacing the sentential premises with graphic arrangements describing the spatial relations between the letters V, X and Z. With this procedure no further linguistic processing was necessary to extract the spatial relations between the objects. Moreover, the processing of the first premise, the second premise and the conclusion was time-locked to the short presentation of the letter arrangements. Thus, we could examine the brain activity elicited by the different phases of the reasoning process. Based on behavioral findings concerning the cognitive processes involved in reasoning (Johnson-Laird, & Byrne, 1991; Evans, Newstead, & Byrne, 1993; Rader, & Sloutsky, 2002), we predicted that there should be different
Weiliang Jin - One of the best experts on this subject based on the ideXlab platform.
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Distribution of millscale on corroded steel bars and penetration of steel corrosion products in concrete
Corrosion Science, 2013Co-Authors: Yuxi Zhao, Weiliang JinAbstract:Abstract This study investigated a reinforced concrete specimen that had deteriorated in an artificial environment for 2 years. The steel/concrete interface and corrosion-induced cracks were observed by SEM to investigate the millscale on the rebar surface and the distribution of rust. The millscale was not further oxidised before the surface cracking of the concrete cover. The penetration of corrosion products into concrete and the formation of a corrosion layer proceeded simultaneously. The rust did not fill the corrosion-induced cracks in concrete. Instead of the Three-Stage Model, a two-stage Model is proposed to describe the concrete cracking process induced by steel corrosion.
Ehab Yamani - One of the best experts on this subject based on the ideXlab platform.
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a three stage Model of the volatility volume relation in the junk bond market during the 2007 2008 financial crisis
Managerial Finance, 2019Co-Authors: Ehab YamaniAbstract:The purpose of this paper is to examine the joint dynamics of volatility–volume relation in the high-yield (junk) corporate bond market during the 2007–2008 financial crisis.,The author proposes a new empirical Model of Three-Stage equations to better estimate the volume–volatility relation that helps in alleviating three econometrical problems. In Stage 1, the author estimates the fitted values of trading volume using a censored regression Model, to alleviate the truncation problems of using Transaction Reporting and Compliance Engine data. In Stage 2, the author calculates the fitted values of bond return volatility using asymmetric Sign-GARCH Model, to control for the asymmetric volatility in return series. In Stage 3, the author uses the fitted values of trading volume from the censored regression Model (Stage 1) and the fitted values of return volatility from the GARCH Model (Stage 2), to better alleviate the endogeneity problems between both variables.,The central finding is that conclusions about the statistical significance and the direction of the volume–volatility relationship in the junk bond market are dependent on the econometric methodology used.,From a practitioner perspective, it is important for professional traders holding positions in fixed income securities in their trading accounts to be aware of their asymmetric time-varying volume–volatility shifting trends. Such knowledge helps traders diversify their positions and manage their portfolios more appropriately.
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A Three-Stage Model of the volatility-volume relation in the Junk bond market during the 2007-2008 financial crisis
Managerial Finance, 2019Co-Authors: Ehab YamaniAbstract:Purpose - The purpose of this paper is to examine the joint dynamics of volatility–volume relation in the high-yield (junk) corporate bond market during the 2007–2008 financial crisis. Design/methodology/approach - The author proposes a new empirical Model of Three-Stage equations to better estimate the volume–volatility relation that helps in alleviating three econometrical problems. In Stage 1, the author estimates the fitted values of trading volume using a censored regression Model, to alleviate the truncation problems of using Transaction Reporting and Compliance Engine data. In Stage 2, the author calculates the fitted values of bond return volatility using asymmetric Sign-GARCH Model, to control for the asymmetric volatility in return series. In Stage 3, the author uses the fitted values of trading volume from the censored regression Model (Stage 1) and the fitted values of return volatility from the GARCH Model (Stage 2), to better alleviate the endogeneity problems between both variables. Findings - The central finding is that conclusions about the statistical significance and the direction of the volume–volatility relationship in the junk bond market are dependent on the econometric methodology used. Originality/value - From a practitioner perspective, it is important for professional traders holding positions in fixed income securities in their trading accounts to be aware of their asymmetric time-varying volume–volatility shifting trends. Such knowledge helps traders diversify their positions and manage their portfolios more appropriately.
Jan E. Staff - One of the best experts on this subject based on the ideXlab platform.
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A three stage Model for the inner engine of GRBs: Prompt emission and early afterglow
International Journal of Modern Physics D, 2008Co-Authors: Jan E. Staff, Brian Niebergal, Rachid OuyedAbstract:We describe a Model within the "quark-nova" scenario to interpret the recent observations of early X-ray afterglows of long gamma-ray bursts (GRBs) with the Swift satellite. This is a Three-Stage Model within the context of a core-collapse supernova. STAGE 1 is an accreting (proto-) neutron star leading to a possible delay between the core collapse and the GRB. STAGE 2 is accretion onto a quark star, launching an ultrarelativistic jet generating the prompt GRB. This jet also creates the afterglow as the jet interacts with the surrounding medium creating an external shock. Slower shells ejected from the quark star (during accretion), can re-energize the external shock leading to a flatter segment in the X-ray afterglow. STAGE 3, which occurs only if the quark star collapses to form a black hole, consists of an accreting black hole. The jet launched in this accretion process interacts with the preceding quark star jet, and could generate the flaring activity frequently seen in early X-ray afterglows. Alternatively, a STAGE 2b can occur in our Model if the quark star does not collapse to a black hole. The quark star in this case can then spin down due to magnetic braking, and the spin down energy may lead to flattening in the X-ray afterglow as well. This Model seems to account for both the energies and the timescales of GRBs, in addition to the newly discovered early X-ray afterglow features.
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A three stage Model for the inner engine of Gamma Ray Burst: Prompt emission and early afterglow
The Astrophysical Journal, 2007Co-Authors: Jan E. Staff, Rachid Ouyed, Manjari BagchiAbstract:We propose a new Model within the ``Quark-nova'' scenario to interpret the recent observations of early afterglows of long Gamma-Ray Bursts (GRB) with the Swift satellite. This is a Three-Stage Model within the context of a core-collapse supernova. Stage 1 is an accreting (proto-) neutron star leading to a possible delay between the core collapse and the GRB. Stage 2 is an accreting quark-star, generating the prompt GRB. Stage 3, which occurs only if the quark-star collapses to form a black-hole, consists of an accreting black-hole. The jet launched in this accretion process interacts with the ejecta from stage 2, and could generate the flaring activity frequently seen in X-ray afterglows. This Model may be able to account for both the energies and the timescales of GRBs, in addition to the newly discovered early X-ray afterglow features.
Manjari Bagchi - One of the best experts on this subject based on the ideXlab platform.
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A three stage Model for the inner engine of Gamma Ray Burst: Prompt emission and early afterglow
The Astrophysical Journal, 2007Co-Authors: Jan E. Staff, Rachid Ouyed, Manjari BagchiAbstract:We propose a new Model within the ``Quark-nova'' scenario to interpret the recent observations of early afterglows of long Gamma-Ray Bursts (GRB) with the Swift satellite. This is a Three-Stage Model within the context of a core-collapse supernova. Stage 1 is an accreting (proto-) neutron star leading to a possible delay between the core collapse and the GRB. Stage 2 is an accreting quark-star, generating the prompt GRB. Stage 3, which occurs only if the quark-star collapses to form a black-hole, consists of an accreting black-hole. The jet launched in this accretion process interacts with the ejecta from stage 2, and could generate the flaring activity frequently seen in X-ray afterglows. This Model may be able to account for both the energies and the timescales of GRBs, in addition to the newly discovered early X-ray afterglow features.
