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Sample records for aucune relation causale

  1. Relating Granger causality to long-term causal effects

    NASA Astrophysics Data System (ADS)

    Smirnov, Dmitry A.; Mokhov, Igor I.

    2015-10-01

    In estimation of causal couplings between observed processes, it is important to characterize coupling roles at various time scales. The widely used Granger causality reflects short-term effects: it shows how strongly perturbations of a current state of one process affect near future states of another process, and it quantifies that via prediction improvement (PI) in autoregressive models. However, it is often more important to evaluate the effects of coupling on long-term statistics, e.g., to find out how strongly the presence of coupling changes the variance of a driven process as compared to an uncoupled case. No general relationships between Granger causality and such long-term effects are known. Here, we pose the problem of relating these two types of coupling characteristics, and we solve it for a class of stochastic systems. Namely, for overdamped linear oscillators, we rigorously derive that the above long-term effect is proportional to the short-term effects, with the proportionality coefficient depending on the prediction interval and relaxation times. We reveal that this coefficient is typically considerably greater than unity so that small normalized PI values may well correspond to quite large long-term effects of coupling. The applicability of the derived relationship to wider classes of systems, its limitations, and its value for further research are discussed. To give a real-world example, we analyze couplings between large-scale climatic processes related to sea surface temperature variations in equatorial Pacific and North Atlantic regions.

  2. Causality and momentum conservation from relative locality

    NASA Astrophysics Data System (ADS)

    Amelino-Camelia, Giovanni; Bianco, Stefano; Brighenti, Francesco; Buonocore, Riccardo Junior

    2015-04-01

    Theories involving curved momentum space, which recently became a topic of interest in the quantum-gravity literature, can, in general, violate many apparently robust aspects of our current description of the laws of physics, including relativistic invariance, locality, causality, and global momentum conservation. Here, we explore some aspects of the pathologies arising in generic theories involving curved momentum space for what concerns causality and momentum conservation. However, we also report results suggesting that when momentum space is maximally symmetric, and the theory is formulated relativistically, most notably including translational invariance with the associated relativity of spacetime locality, momentum is globally conserved and there is no violation of causality.

  3. Causality principles in solar activity -climate relations.

    NASA Astrophysics Data System (ADS)

    Stauning, Peter

    The relations between solar activity and the terrestrial climate have quite often been inves-tigated. In most cases the analyses have been based on comparisons between time series of solar activity parameters, for instance sunspot numbers, and terrestrial climate parameters, for instance global temperatures. However, many of the reported close relations are based on skilfully manipulated data and neglect of basic causality principles. For cause-effect relations to be reliably established, the variations in the causative function must obviously happen prior to the related effects. Thus it is problematic to use, for instance, running averages of parameters, if the result depends too much on posterior elements of the causative time series or precursory elements of the effects. Even more neglected are the causality principles for cause-effect rela-tions with a strongly varying source function, like for instance the 11 year solar activity cycle. In such cases damping of source variations by smoothing data series, introduces additional im-plied delays, which should be considered in the judgement of apparent correlations between the processed time series of cause and effect parameters. The presentation shall illustrate causal-ity relations between solar activity and terrestrial climate parameters and discuss examples of frequently quoted solar activity-climate relations, which violate basic causality principles.

  4. Are bruxism and the bite causally related?

    PubMed

    Lobbezoo, F; Ahlberg, J; Manfredini, D; Winocur, E

    2012-07-01

    In the dental profession, the belief that bruxism and dental (mal-)occlusion ('the bite') are causally related is widespread. The aim of this review was to critically assess the available literature on this topic. A PubMed search of the English-language literature, using the query 'Bruxism [Majr] AND (Dental Occlusion [Majr] OR Malocclusion [Majr])', yielded 93 articles, of which 46 papers were finally included in the present review*. Part of the included publications dealt with the possible associations between bruxism and aspects of occlusion, from which it was concluded that neither for occlusal interferences nor for factors related to the anatomy of the oro-facial skeleton, there is any evidence available that they are involved in the aetiology of bruxism. Instead, there is a growing awareness of other factors (viz. psychosocial and behavioural ones) being important in the aetiology of bruxism. Another part of the included papers assessed the possible mediating role of occlusion between bruxism and its purported consequences (e.g. tooth wear, loss of periodontal tissues, and temporomandibular pain and dysfunction). Even though most dentists agree that bruxism may have several adverse effects on the masticatory system, for none of these purported adverse effects, evidence for a mediating role of occlusion and articulation has been found to date. Hence, based on this review, it should be concluded that to date, there is no evidence whatsoever for a causal relationship between bruxism and the bite. PMID:22489928

  5. Preschoolers' Understanding of Temporal and Causal Relations.

    ERIC Educational Resources Information Center

    Sharp, Kay Colby

    1982-01-01

    Two experiments investigated psychological factors determining preschoolers' success or failure on a sequence-completion task involving temporal and causal ordering of events. Overall findings demonstrate that while preschoolers do understand temporal/causal relationships, their abilities are dependent on process variables demanded by the task…

  6. Causal Coherence Relations and Levels of Discourse Representation

    ERIC Educational Resources Information Center

    Mulder, Gerben; Sanders, Ted J. M.

    2012-01-01

    This study focused on the cognitive representation of causal coherence relations linguistically marked with the connective "because." This article investigated whether these local causal relations are represented both at the level of the textbase and the situation model. Following earlier studies investigating the psychological validity of levels…

  7. Causal Relations Drive Young Children's Induction, Naming, and Categorization

    ERIC Educational Resources Information Center

    Opfer, John E.; Bulloch, Megan J.

    2007-01-01

    A number of recent models and experiments have suggested that evidence of early category-based induction is an artifact of perceptual cues provided by experimenters. We tested these accounts against the prediction that different relations (causal versus non-causal) determine the types of perceptual similarity by which children generalize. Young…

  8. Causality

    NASA Astrophysics Data System (ADS)

    Pearl, Judea

    2000-03-01

    Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

  9. Melting chocolate and melting snowmen: analogical reasoning and causal relations.

    PubMed

    Goswami, U; Brown, A L

    1990-04-01

    Children's performance in the classical a:b::c:d analogy task is traditionally very poor prior to the Piagetian stage of formal operations. The interpretation has been that the ability to reason about higher-order relations (the relations between the a:b and c:d parts of the analogy) is late-developing. However, an alternative possibility is that the relations used to date in the analogies are too difficult for younger children. Two experiments presented children aged 3, 4 and 6 years with a:b::c:d analogies which were based on relations of physical causality such as melting and cutting, for example chocolate bar:melted chocolate::snowman:melted snowman. Understanding of these particular causal relations is known to develop between the ages of 3 and 4 years. It was found that even 3-year-olds could solve the classical analogies if they understood the causal relations on which they were based. PMID:2340713

  10. Relative entropy, mixed gauge-gravitational anomaly and causality

    NASA Astrophysics Data System (ADS)

    Bhattacharyya, Arpan; Cheng, Long; Hung, Ling-Yan

    2016-07-01

    In this note we explored the holographic relative entropy in the presence of the 5d Chern-Simons term, which introduces a mixed gauge-gravity anomaly to the dual CFT. The theory trivially satisfies an entanglement first law. However, to quadratic order in perturbations of the stress tensor T and current density J , there is a mixed contributionto the relative entropy bi-linear in T and J , signalling a potential violation of the positivity of the relative entropy. Miraculously, the term vanishes up to linear order in a derivative expansion. This prompted a closer inspection on a different consistency check, that involves time-delay of a graviton propagating in a charged background, scattered via a coupling supplied by the Chern-Simons term. The analysis suggests that the time-delay can take either sign, potentially violating causality for any finite value of the CS coupling.

  11. Geomagnetic field and climate: Causal relations with some atmospheric variables

    NASA Astrophysics Data System (ADS)

    Kilifarska, N. A.; Bakhmutov, V. G.; Mel'nik, G. V.

    2015-09-01

    The relationship between climatic parameters and the Earth's magnetic field has been reported by many authors. However, the absence of a feasible mechanism accounting for this relationship has impeded progress in this research field. Based on the instrumental observations, we reveal the spatiotemporal relationship between the key structures in the geomagnetic field, surface air temperature and pressure fields, ozone, and the specific humidity near the tropopause. As one of the probable explanations of these correlations, we suggest the following chain of the causal relations: (1) modulation of the intensity and penetration depth of energetic particles (galactic cosmic rays (GCRs)) in the Earth's atmosphere by the geomagnetic field; (2) the distortion of the ozone density near the tropopause under the action of GCRs; (3) the change in temperature near the tropopause due to the high absorbing capacity of ozone; (4) the adjustment of the extra-tropical upper tropospheric static stability and, consequently, specific humidity, to the modified tropopause temperature; and (5) the change in the surface air temperature due to the increase/decrease of the water vapor greenhouse effect.

  12. Network Representations of Causal Relations in Memory for Narrative Texts: Evidence from Primed Recognition.

    ERIC Educational Resources Information Center

    van den Broek, Paul; Lorch, Robert F., Jr.

    1993-01-01

    Investigates how adult readers represent causal relations among events in a narrative, specifically by testing two models of text comprehension, the linear chain of text model versus the network model. Provides support for a network model of the representation of causal relations in narratives. (HB)

  13. The causal relation between human papillomavirus and cervical cancer

    PubMed Central

    Bosch, F X; Lorincz, A; Muñoz, N; Meijer, C J L M; Shah, K V

    2002-01-01

    The causal role of human papillomavirus infections in cervical cancer has been documented beyond reasonable doubt. The association is present in virtually all cervical cancer cases worldwide. It is the right time for medical societies and public health regulators to consider this evidence and to define its preventive and clinical implications. A comprehensive review of key studies and results is presented. PMID:11919208

  14. Is there a causal relation between mathematical creativity and mathematical problem-solving performance?

    NASA Astrophysics Data System (ADS)

    Tyagi, Tarun Kumar

    2016-04-01

    The relationship between mathematical creativity (MC) and mathematical problem-solving performance (MP) has often been studied but the causal relation between these two constructs has yet to be clearly reported. The main purpose of this study was to define the causal relationship between MC and MP. Data from a representative sample of 480 eighth-grade students were analysed using a cross-lagged panel correlation (CLPC) design. CLPC attempts to rule out plausible alternative explanation of a causal effect. The result suggests that significant predominant causal relationship was found between MC and MP. It indicates that MP was found to be a cause of MC than the converse.

  15. [Historical causality and relative contemporaneity Einsteinian relativity in the historical sciences].

    PubMed

    Bontems, Vincent

    2014-01-01

    The construction of historical frame of reference based on the distinction between and articulation of phenomenological and chronological times. As it relativises the notion of simultaneity and inverts its relation to causality, the special theory of relativity can induce analogous modes of reflection on the themes of "contemporaneity" in the history of art (Panofsky) and in epistemology (Bachelard). This "relativist" method, often misunderstood, sheds light on both historical and presentist methods. PMID:24871883

  16. Is There a Causal Relation between Mathematical Creativity and Mathematical Problem-Solving Performance?

    ERIC Educational Resources Information Center

    Tyagi, Tarun Kumar

    2016-01-01

    The relationship between mathematical creativity (MC) and mathematical problem-solving performance (MP) has often been studied but the causal relation between these two constructs has yet to be clearly reported. The main purpose of this study was to define the causal relationship between MC and MP. Data from a representative sample of 480…

  17. Statistical Approaches for Enhancing Causal Interpretation of the M to Y Relation in Mediation Analysis

    PubMed Central

    MacKinnon, David P.; Pirlott, Angela G.

    2016-01-01

    Statistical mediation methods provide valuable information about underlying mediating psychological processes, but the ability to infer that the mediator variable causes the outcome variable is more complex than widely known. Researchers have recently emphasized how violating assumptions about confounder bias severely limits causal inference of the mediator to dependent variable relation. Our article describes and addresses these limitations by drawing on new statistical developments in causal mediation analysis. We first review the assumptions underlying causal inference and discuss three ways to examine the effects of confounder bias when assumptions are violated. We then describe four approaches to address the influence of confounding variables and enhance causal inference, including comprehensive structural equation models, instrumental variable methods, principal stratification, and inverse probability weighting. Our goal is to further the adoption of statistical methods to enhance causal inference in mediation studies. PMID:25063043

  18. Transitive closure of subsumption and causal relations in a large ontology of radiological diagnosis.

    PubMed

    Kahn, Charles E

    2016-06-01

    The Radiology Gamuts Ontology (RGO)-an ontology of diseases, interventions, and imaging findings-was developed to aid in decision support, education, and translational research in diagnostic radiology. The ontology defines a subsumption (is_a) relation between more general and more specific terms, and a causal relation (may_cause) to express the relationship between disorders and their possible imaging manifestations. RGO incorporated 19,745 terms with their synonyms and abbreviations, 1768 subsumption relations, and 55,558 causal relations. Transitive closure was computed iteratively; it yielded 2154 relations over subsumption and 1,594,896 relations over causality. Five causal cycles were discovered, all with path length of no more than 5. The graph-theoretic metrics of in-degree and out-degree were explored; the most useful metric to prioritize modification of the ontology was found to be the product of the in-degree of transitive closure over subsumption and the out-degree of transitive closure over causality. Two general types of error were identified: (1) causal assertions that used overly general terms because they implicitly assumed an organ-specific context and (2) subsumption relations where a site-specific disorder was asserted to be a subclass of the general disorder. Transitive closure helped identify incorrect assertions, prioritized and guided ontology revision, and aided resources that applied the ontology's knowledge. PMID:27005590

  19. Intolerance of uncertainty, causal uncertainty, causal importance, self-concept clarity and their relations to generalized anxiety disorder.

    PubMed

    Kusec, Andrea; Tallon, Kathleen; Koerner, Naomi

    2016-06-01

    Although numerous studies have provided support for the notion that intolerance of uncertainty plays a key role in pathological worry (the hallmark feature of generalized anxiety disorder (GAD)), other uncertainty-related constructs may also have relevance for the understanding of individuals who engage in pathological worry. Three constructs from the social cognition literature, causal uncertainty, causal importance, and self-concept clarity, were examined in the present study to assess the degree to which these explain unique variance in GAD, over and above intolerance of uncertainty. N = 235 participants completed self-report measures of trait worry, GAD symptoms, and uncertainty-relevant constructs. A subgroup was subsequently classified as low in GAD symptoms (n = 69) or high in GAD symptoms (n = 54) based on validated cut scores on measures of trait worry and GAD symptoms. In logistic regressions, only elevated intolerance of uncertainty and lower self-concept clarity emerged as unique correlates of high (vs. low) GAD symptoms. The possible role of self-concept uncertainty in GAD and the utility of integrating social cognition theories and constructs into clinical research on intolerance of uncertainty are discussed. PMID:27113431

  20. Making sense of (exceptional) causal relations. A cross-cultural and cross-linguistic study

    PubMed Central

    Le Guen, Olivier; Samland, Jana; Friedrich, Thomas; Hanus, Daniel; Brown, Penelope

    2015-01-01

    In order to make sense of the world, humans tend to see causation almost everywhere. Although most causal relations may seem straightforward, they are not always construed in the same way cross-culturally. In this study, we investigate concepts of “chance,” “coincidence,” or “randomness” that refer to assumed relations between intention, action, and outcome in situations, and we ask how people from different cultures make sense of such non-law-like connections. Based on a framework proposed by Alicke (2000), we administered a task that aims to be a neutral tool for investigating causal construals cross-culturally and cross-linguistically. Members of four different cultural groups, rural Mayan Yucatec and Tseltal speakers from Mexico and urban students from Mexico and Germany, were presented with a set of scenarios involving various types of causal and non-causal relations and were asked to explain the described events. Three links varied as to whether they were present or not in the scenarios: Intention-to-Action, Action-to-Outcome, and Intention-to-Outcome. Our results show that causality is recognized in all four cultural groups. However, how causality and especially non-law-like relations are interpreted depends on the type of links, the cultural background and the language used. In all three groups, Action-to-Outcome is the decisive link for recognizing causality. Despite the fact that the two Mayan groups share similar cultural backgrounds, they display different ideologies regarding concepts of non-law-like relations. The data suggests that the concept of “chance” is not universal, but seems to be an explanation that only some cultural groups draw on to make sense of specific situations. Of particular importance is the existence of linguistic concepts in each language that trigger ideas of causality in the responses from each cultural group. PMID:26579028

  1. Is preschool executive function causally related to academic achievement?

    PubMed

    Willoughby, Michael T; Kupersmidt, Janis B; Voegler-Lee, Mary E

    2012-01-01

    The primary objective of this study was to reevaluate the well-established result that preschoolers' performance on executive function tasks are positively associated with their performance on academic achievement tests. The current study replicated the previously established concurrent associations between children's performance on EF tasks and academic achievement tests. Specifically, children's performance on measures of inhibitory and motor control were positively associated with their performance on tests of reading, writing, and mathematics achievement (rs = .2-.5); moreover, although diminished in magnitude, most of these associations held up even after including an earlier measure of academic achievement as a covariate (rs = .1-.3). However, the application of an alternative analytic method, fixed effects analysis, a method that capitalizes on repeated measures data to control for all time stable measured and unmeasured covariates, rendered the apparent positive associations between executive function and academic achievement nonsignificant (rs = .0-.1). Taken together, these results suggest that the well-replicated association between executive function abilities and academic achievement may be spurious. Results are discussed with respect to the importance of utilizing analytic methods and research designs that facilitate strong causal inferences between executive function and academic achievement in early childhood, as well as the limitations of making curriculum development recommendations and/or public policy decisions based on studies that have failed to do so. PMID:21707258

  2. An Analysis of the Ontological Causal Relation in Physics and Its Educational Implications

    ERIC Educational Resources Information Center

    Cheong, Yong Wook

    2016-01-01

    An ontological causal relation is a quantified relation between certain interactions and changes in corresponding properties. Key ideas in physics, such as Newton's second law and the first law of thermodynamics, are representative examples of these relations. In connection with the teaching and learning of these relations, this study investigated…

  3. Effects of Increased Psychiatric Treatment Contact and Acculturation on the Causal Beliefs of Chinese Immigrant Relatives of Individuals with Psychosis

    PubMed Central

    Lo, Graciete; Tu, Ming; Wu, Olivia; Anglin, Deidre; Saw, Anne; Chen, Fang-pei

    2016-01-01

    Encounters with Western psychiatric treatment and acculturation may influence causal beliefs of psychiatric illness endorsed by Chinese immigrant relatives, thus affecting help-seeking. We examined causal beliefs held by forty-six Chinese immigrant relatives and found that greater acculturation was associated with an increased number of causal beliefs. Further, as Western psychiatric treatment and acculturation increased, causal models expanded to incorporate biological/physical causes. However, frequency of Chinese immigrant relatives' endorsing spiritual beliefs did not appear to change with acculturation. Clinicians might thus account for spiritual beliefs in treatment even after acculturation increases and biological causal models proliferate. PMID:27127454

  4. Perceived Causal Relations: Novel Methodology for Assessing Client Attributions about Causal Associations between Variables Including Symptoms and Functional Impairment

    ERIC Educational Resources Information Center

    Frewen, Paul A.; Allen, Samantha L.; Lanius, Ruth A.; Neufeld, Richard W. J.

    2012-01-01

    Researchers have argued that the investigation of causal interrelationships between symptoms may help explain the high comorbidity rate between certain psychiatric disorders. Clients' own attributions concerning the causal interrelationships linking the co-occurrence of their symptoms represent data that may inform their clinical case…

  5. Is there a relation between the 2D Causal Set action and the Lorentzian Gauss-Bonnet theorem?

    NASA Astrophysics Data System (ADS)

    Benincasa, Dionigi M. T.

    2011-07-01

    We investigate the relation between the two dimensional Causal Set action, Script S, and the Lorentzian Gauss-Bonnet theorem (LGBT). We give compelling reasons why the answer to the title's question is no. In support of this point of view we calculate the causal set inspired action of causal intervals in some two dimensional spacetimes: Minkowski, the flat cylinder and the flat trousers.

  6. Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables.

    PubMed

    Yin, Yu; Yao, Dezhong

    2016-01-01

    The main concept behind causality involves both statistical conditions and temporal relations. However, current approaches to causal inference, focusing on the probability vs. conditional probability contrast, are based on model functions or parametric estimation. These approaches are not appropriate when addressing non-stationary variables. In this work, we propose a causal inference approach based on the analysis of Events of Relations (CER). CER focuses on the temporal delay relation between cause and effect, and a binomial test is established to determine whether an "event of relation" with a non-zero delay is significantly different from one with zero delay. Because CER avoids parameter estimation of non-stationary variables per se, the method can be applied to both stationary and non-stationary signals. PMID:27389921

  7. Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables

    PubMed Central

    Yin, Yu; Yao, Dezhong

    2016-01-01

    The main concept behind causality involves both statistical conditions and temporal relations. However, current approaches to causal inference, focusing on the probability vs. conditional probability contrast, are based on model functions or parametric estimation. These approaches are not appropriate when addressing non-stationary variables. In this work, we propose a causal inference approach based on the analysis of Events of Relations (CER). CER focuses on the temporal delay relation between cause and effect, and a binomial test is established to determine whether an “event of relation” with a non-zero delay is significantly different from one with zero delay. Because CER avoids parameter estimation of non-stationary variables per se, the method can be applied to both stationary and non-stationary signals. PMID:27389921

  8. How Hypertext Reading Sequences Affect Understanding of Causal and Temporal Relations in Story Comprehension

    ERIC Educational Resources Information Center

    Urakami, Jacqueline; Krems, Josef F.

    2012-01-01

    The goal of this study is to examine the comprehension of global causal and temporal relations between events that are represented in single hypertext documents. In two experiments we examined how reading sequences of hypertext nodes affects the establishment of event relations and how this process can be supported by advanced organizers that…

  9. Perceived causal relations between anxiety, posttraumatic stress and depression: extension to moderation, mediation, and network analysis

    PubMed Central

    Frewen, Paul A.; Schmittmann, Verena D.; Bringmann, Laura F.; Borsboom, Denny

    2013-01-01

    Background Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. Objectives The present study utilized Perceived Causal Relations (PCR) scaling in order to assess participants’ own attributions concerning whether and to what degree these co-occurring problems may be causally interrelated. Methods 288 young adults rated the frequency and respective PCR scores associating their symptoms of posttraumatic reexperiencing, depression, anxiety, and guilt-shame. Results PCR scores were found to moderate associations between the frequency of posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame. Network analyses showed that the number of feedback loops between PCR scores was positively associated with symptom frequencies. Conclusion Results tentatively support the interpretation of PCR scores as moderators of the association between different psychological problems, and lend support to the hypothesis that increased symptom frequencies are observed in the presence of an increased number of causal feedback loops between symptoms. Additionally, a perceived causal role for the reexperiencing of traumatic memories in exacerbating emotional disturbance was identified. PMID:24003362

  10. Semi-supervised learning of causal relations in biomedical scientific discourse

    PubMed Central

    2014-01-01

    Background The increasing number of daily published articles in the biomedical domain has become too large for humans to handle on their own. As a result, bio-text mining technologies have been developed to improve their workload by automatically analysing the text and extracting important knowledge. Specific bio-entities, bio-events between these and facts can now be recognised with sufficient accuracy and are widely used by biomedical researchers. However, understanding how the extracted facts are connected in text is an extremely difficult task, which cannot be easily tackled by machinery. Results In this article, we describe our method to recognise causal triggers and their arguments in biomedical scientific discourse. We introduce new features and show that a self-learning approach improves the performance obtained by supervised machine learners to 83.47% for causal triggers. Furthermore, the spans of causal arguments can be recognised to a slightly higher level that by using supervised or rule-based methods that have been employed before. Conclusion Exploiting the large amount of unlabelled data that is already available can help improve the performance of recognising causal discourse relations in the biomedical domain. This improvement will further benefit the development of multiple tasks, such as hypothesis generation for experimental laboratories, contradiction detection, and the creation of causal networks. PMID:25559746

  11. Causal estimation of neural and overall baroreflex sensitivity in relation to carotid artery stiffness.

    PubMed

    Lipponen, Jukka A; Tarvainen, Mika P; Laitinen, Tomi; Karjalainen, Pasi A; Vanninen, Joonas; Koponen, Timo; Laitinen, Tiina M

    2013-12-01

    Continuous electrocardiogram, blood pressure and carotid artery ultrasound video were analyzed from 15 diabetics and 28 healthy controls. By using these measurements artery elasticity, overall baroreflex sensitivity (BRS) assessed between RR and systolic blood pressure variation, and neural BRS assessed between RR and artery diameter variation were estimated. In addition, BRS was estimated using traditional and causal methods which enable separation of feedforward and feedback variation. The aim of this study was to analyze overall and neural BRS in relation to artery stiffness and to validate the causal BRS estimation method in assessing these two types of BRS within the study population. The most significant difference between the healthy and diabetic groups (p < 0.0007) was found for the overall BRS estimated using the causal method. The difference between the groups was also significant for neural BRS (p < 0.0018). However neural BRS was normal in some old diabetics, which indicates normal functioning of autonomic nervous system (ANS), even though the elasticity in arteries of these subjects was reduced. The noncausal method overestimated neural BRS in low BRS values when compared to causal BRS. In conclusion, neural BRS estimated using the causal method is proposed as the best marker of ANS functioning. PMID:24168896

  12. An Analysis of the Ontological Causal Relation in Physics and Its Educational Implications

    NASA Astrophysics Data System (ADS)

    Cheong, Yong Wook

    2016-06-01

    An ontological causal relation is a quantified relation between certain interactions and changes in corresponding properties. Key ideas in physics, such as Newton's second law and the first law of thermodynamics, are representative examples of these relations. In connection with the teaching and learning of these relations, this study investigated three issues: the appropriate view concerning ontological category, the role and status of ontological causal relations, and university students' understanding of the role and status of these relations. Concerning the issue of proper ontology, this study suggests an alternative view that distinguishes between interaction and property at the macroscopic level, in contrast to Chi and colleagues' influential view. Concerning the role and status of the relations, we conclude that fundamental ontological causal relations should be regarded as knowledge at the core of relevant physics theories. However, upon analysis of participants' responses, this study finds that university students' views on the status of the heat capacity relation and Newton's second law are quite different. Several possible educational implications of these results are discussed.

  13. An Analysis of the Ontological Causal Relation in Physics and Its Educational Implications

    NASA Astrophysics Data System (ADS)

    Cheong, Yong Wook

    2016-08-01

    An ontological causal relation is a quantified relation between certain interactions and changes in corresponding properties. Key ideas in physics, such as Newton's second law and the first law of thermodynamics, are representative examples of these relations. In connection with the teaching and learning of these relations, this study investigated three issues: the appropriate view concerning ontological category, the role and status of ontological causal relations, and university students' understanding of the role and status of these relations. Concerning the issue of proper ontology, this study suggests an alternative view that distinguishes between interaction and property at the macroscopic level, in contrast to Chi and colleagues' influential view. Concerning the role and status of the relations, we conclude that fundamental ontological causal relations should be regarded as knowledge at the core of relevant physics theories. However, upon analysis of participants' responses, this study finds that university students' views on the status of the heat capacity relation and Newton's second law are quite different. Several possible educational implications of these results are discussed.

  14. Do Capuchin Monkeys (Cebus apella) Diagnose Causal Relations in the Absence of a Direct Reward?

    PubMed Central

    Edwards, Brian J.; Rottman, Benjamin M.; Shankar, Maya; Betzler, Riana; Chituc, Vladimir; Rodriguez, Ricardo; Silva, Liara; Wibecan, Leah; Widness, Jane; Santos, Laurie R.

    2014-01-01

    We adapted a method from developmental psychology [1] to explore whether capuchin monkeys (Cebus apella) would place objects on a “blicket detector” machine to diagnose causal relations in the absence of a direct reward. Across five experiments, monkeys could place different objects on the machine and obtain evidence about the objects’ causal properties based on whether each object “activated” the machine. In Experiments 1–3, monkeys received both audiovisual cues and a food reward whenever the machine activated. In these experiments, monkeys spontaneously placed objects on the machine and succeeded at discriminating various patterns of statistical evidence. In Experiments 4 and 5, we modified the procedure so that in the learning trials, monkeys received the audiovisual cues when the machine activated, but did not receive a food reward. In these experiments, monkeys failed to test novel objects in the absence of an immediate food reward, even when doing so could provide critical information about how to obtain a reward in future test trials in which the food reward delivery device was reattached. The present studies suggest that the gap between human and animal causal cognition may be in part a gap of motivation. Specifically, we propose that monkey causal learning is motivated by the desire to obtain a direct reward, and that unlike humans, monkeys do not engage in learning for learning’s sake. PMID:24586347

  15. The Processing of Causal and Hierarchical Relations in Semantic Memory as Revealed by N400 and Frontal Negativity

    PubMed Central

    Lei, Yi; Li, Hong

    2015-01-01

    Most current studies investigating semantic memory have focused on associative (ring-emerald) or taxonomic relations (bird-sparrow). Little is known about the question of how causal relations (virus- epidemic) are stored and accessed in semantic memory. The goal of this study was to examine the processing of causally related, general associatively related and hierarchically related word pairs when participants were required to evaluate whether pairs of words were related in any way. The ERP data showed that the N400 amplitude (200-500ms) elicited by unrelated related words was more negative than all related words. Furthermore, the late frontal distributed negativity (500-700ms) elicited by causally related words was smaller than hierarchically related words, but not for general associated words. These results suggested the processing of causal relations and hierarchical relations in semantic memory recruited different degrees of cognitive resources, especially for role binding. PMID:26148338

  16. The Processing of Causal and Hierarchical Relations in Semantic Memory as Revealed by N400 and Frontal Negativity.

    PubMed

    Liang, Xiuling; Chen, Qingfei; Lei, Yi; Li, Hong

    2015-01-01

    Most current studies investigating semantic memory have focused on associative (ring-emerald) or taxonomic relations (bird-sparrow). Little is known about the question of how causal relations (virus-epidemic) are stored and accessed in semantic memory. The goal of this study was to examine the processing of causally related, general associatively related and hierarchically related word pairs when participants were required to evaluate whether pairs of words were related in any way. The ERP data showed that the N400 amplitude (200-500 ms) elicited by unrelated related words was more negative than all related words. Furthermore, the late frontal distributed negativity (500-700 ms) elicited by causally related words was smaller than hierarchically related words, but not for general associated words. These results suggested the processing of causal relations and hierarchical relations in semantic memory recruited different degrees of cognitive resources, especially for role binding. PMID:26148338

  17. Causal reasoning with forces

    PubMed Central

    Wolff, Phillip; Barbey, Aron K.

    2015-01-01

    Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611

  18. Sex differences in the inference and perception of causal relations within a video game

    PubMed Central

    Young, Michael E.

    2014-01-01

    The learning of immediate causation within a dynamic environment was examined. Participants encountered seven decision points in which they needed to choose, which of three possible candidates was the cause of explosions in the environment. Each candidate was firing a weapon at random every few seconds, but only one of them produced an immediate effect. Some participants showed little learning, but most demonstrated increases in accuracy across time. On average, men showed higher accuracy and shorter latencies that were not explained by differences in self-reported prior video game experience. This result suggests that prior reports of sex differences in causal choice in the game are not specific to situations involving delayed or probabilistic causal relations. PMID:25202293

  19. On the violation of causal, emotional, and locative inferences: An event-related potentials study.

    PubMed

    Rodríguez-Gómez, Pablo; Sánchez-Carmona, Alberto; Smith, Cybelle; Pozo, Miguel A; Hinojosa, José A; Moreno, Eva M

    2016-07-01

    Previous event-related potential studies have demonstrated the online generation of inferences during reading for comprehension tasks. The present study contrasted the brainwave patterns of activity to the fulfilment or violation of various types of inferences (causal, emotional, locative). Relative to inference congruent sentence endings, a typical centro-parietal N400 was elicited for the violation of causal and locative inferences. This N400 effect was initially absent for emotional inferences, most likely due to their lower cloze probability. Between 500 and 750ms, a larger frontal positivity (pN400FP) was elicited by inference incongruent sentence endings in the causal condition. In emotional sentences, both inference congruent and incongruent endings exerted this frontally distributed late positivity. For the violation of locative inferences, the larger positivity was only marginally significant over left posterior scalp locations. Thus, not all inference eliciting sentences evoked a similar pattern of ERP responses. We interpret and discuss our results in line with recent views on what the N400, the P600 and the pN400FP brainwave potentials index. PMID:27150706

  20. Tropical convective onset statistics and establishing causality in the water vapor-precipitation relation

    NASA Astrophysics Data System (ADS)

    Neelin, J. D.; Kuo, Y. H.; Schiro, K. A.; Langenbrunner, B.; Mechoso, C. R.; Sahany, S.; Bernstein, D. N.

    2015-12-01

    Previous work by various authors has pointed to the role of humidity in the lower free troposphere in affecting the onset of deep convection in the tropics. Empirical relations between column water vapor and the onset of precipitation have been inferred to be related to this. Evidence includes deep-convective conditional instability calculations for entraining plumes, in which the lower free-tropospheric environment affects the onset of deep convection due to the impact on buoyancy of turbulent entrainment of dry versus moist air. Tropical Western Pacific in situ observations, and tropical ocean basin satellite retrievals in comparison to climate model diagnostics each indicate that substantial entrainment is required to explain the observed relationship. In situ observations from the GoAmazon field campaign confirm that the basic relationship holds over tropical land much as it does over tropical ocean (although with greater additional sensitivity to boundary layer variations and to freezing processes). The relationship between deep convection and water vapor is, however, a two-way street, with convection moistening the free troposphere. One might thus argue that there has not yet been a smoking gun in terms of establishing the causality of the precipitation-water vapor relationship. Parameter perturbation experiments in the coupled Community Earth System Model show that when the deep convective scheme has low values of entrainment, the set of statistics associated with the transition to deep convection are radically altered, and the observed pickup of precipitation with column water vapor is no longer seen. In addition to cementing the dominant direction of causality in the fast timescale precipitation-column water vapor relationship, the results point to impacts of this mechanism on the climatology. Because at low entrainment the convection can fire before the lower troposphere is moistened, the climatology of water vapor remains lower than observed. These

  1. Relativistic causality

    NASA Astrophysics Data System (ADS)

    Valente, Giovanni; Owen Weatherall, James

    2014-11-01

    Relativity theory is often taken to include, or to imply, a prohibition on superluminal propagation of causal processes. Yet, what exactly the prohibition on superluminal propagation amounts to and how one should deal with its possible violation have remained open philosophical problems, both in the context of the metaphysics of causation and the foundations of physics. In particular, recent work in philosophy of physics has focused on the causal structure of spacetime in relativity theory and on how this causal structure manifests itself in our most fundamental theories of matter. These topics were the subject of a workshop on "Relativistic Causality in Quantum Field Theory and General Relativity" that we organized (along with John Earman) at the Center for Philosophy of Science in Pittsburgh on April 5-7, 2013. The present Special Issue comprises contributions by speakers in that workshop as well as several other experts exploring different aspects of relativistic causality. We are grateful to the journal for hosting this Special Issue, to the journal's managing editor, Femke Kuiling, for her help and support in putting the issue together, and to the authors and the referees for their excellent work.

  2. Great apes and children infer causal relations from patterns of variation and covariation.

    PubMed

    Völter, Christoph J; Sentís, Inés; Call, Josep

    2016-10-01

    We investigated whether nonhuman great apes (N=23), 2.5-year-old (N=20), and 3-year-old children (N=40) infer causal relations from patterns of variation and covariation by adapting the blicket detector paradigm for apes. We presented chimpanzees (Pan troglodytes), bonobos (Pan paniscus), orangutans (Pongo abelii), gorillas (Gorilla gorilla), and children (Homo sapiens) with a novel reward dispenser, the blicket detector. The detector was activated by inserting specific (yet randomly determined) objects, the so-called blickets. Once activated a reward was released, accompanied by lights and a short tone. Participants were shown different patterns of variation and covariation between two different objects and the activation of the detector. When subsequently choosing between one of the two objects to activate the detector on their own all species, except gorillas (who failed the training), took these patterns of correlation into account. In particular, apes and 2.5-year-old children ignored objects whose effect on the detector completely depended on the presence of another object. Follow-up experiments explored whether the apes and children were also able to re-evaluate evidence retrospectively. Only children (3-year-olds in particular) were able to make such retrospective inferences about causal structures from observing the effects of the experimenter's actions. Apes succeeded here only when they observed the effects of their own interventions. Together, this study provides evidence that apes, like young children, accurately infer causal structures from patterns of (co)variation and that they use this information to inform their own interventions. PMID:27343481

  3. Children's developing understanding of the relation between variable causal efficacy and mechanistic complexity.

    PubMed

    Erb, Christopher D; Buchanan, David W; Sobel, David M

    2013-12-01

    Two experiments investigated 3-4-year-olds' ability to infer the causal mechanisms for a pair of lights. In both experiments the exterior of the two lights appeared identical. In Experiment 1, one light displayed a stable activation pattern of a single color while the other light displayed a variable pattern of activation by cycling through a series of different colors (i.e., a more varied effect). Children were asked to judge which light had a more complex internal structure. Four-year-olds were more likely to match the light with the more variable effect with a more complex internal mechanism and the light with the more stable effect with a less complex mechanism. Three-year-olds' responses were at chance. Experiment 2 replicated this finding when the activation patterns of the two lights were described verbally but never demonstrated. Taken together, these results suggest that 4-year-olds appreciate that the variability of an object's causal efficacy is related to the complexity of its internal mechanistic structure. PMID:24041835

  4. Nonultralocality and causality in the relational framework of canonical quantum gravity

    NASA Astrophysics Data System (ADS)

    de Vegvar, P. G. N.

    2016-05-01

    The relational framework of canonical quantum gravity with nonultralocal constraints is explored. After demonstrating the absence of anomalies, a spatially discretized version of the relational framework is introduced. This allows the application of Lieb-Robinson bounds to on-shell monotonic gauge flow when there is a continuous external "time" parameter. An explicit Lieb-Robinson bound is derived for the differential on-shell evolution of the operator norm of the commutator of discretized Dirac observables, demonstrating how a local light conelike causal structure emerges. Ultralocal constraints do not permit such a structure to arise via Lieb-Robinson bounds. Gauge and (3 +1 )-diffeomorphism invariance of the light cone is discussed along with the issues of quantum fluctuations, the nature of the nonlocalities, the spatial continuum limit, and the possible links to noncommutative geometry.

  5. Direct and indirect causal effects of heterozygosity on fitness-related traits in Alpine ibex

    PubMed Central

    Brambilla, Alice; Biebach, Iris; Bassano, Bruno; Bogliani, Giuseppe; von Hardenberg, Achaz

    2015-01-01

    Heterozygosity–fitness correlations (HFCs) are a useful tool to investigate the effects of inbreeding in wild populations, but are not informative in distinguishing between direct and indirect effects of heterozygosity on fitness-related traits. We tested HFCs in male Alpine ibex (Capra ibex) in a free-ranging population (which suffered a severe bottleneck at the end of the eighteenth century) and used confirmatory path analysis to disentangle the causal relationships between heterozygosity and fitness-related traits. We tested HFCs in 149 male individuals born between 1985 and 2009. We found that standardized multi-locus heterozygosity (MLH), calculated from 37 microsatellite loci, was related to body mass and horn growth, which are known to be important fitness-related traits, and to faecal egg counts (FECs) of nematode eggs, a proxy of parasite resistance. Then, using confirmatory path analysis, we were able to show that the effect of MLH on horn growth was not direct but mediated by body mass and FEC. HFCs do not necessarily imply direct genetic effects on fitness-related traits, which instead can be mediated by other traits in complex and unexpected ways. PMID:25392468

  6. THE NON-CAUSAL ORIGIN OF THE BLACK-HOLE-GALAXY SCALING RELATIONS

    SciTech Connect

    Jahnke, Knud; Maccio, Andrea V. E-mail: maccio@mpia.de

    2011-06-20

    We show that the M{sub BH}-M{sub bulge} scaling relations observed from the local to the high-z universe can be largely or even entirely explained by a non-causal origin, i.e., they do not imply the need for any physically coupled growth of black hole (BH) and bulge mass, for example, through feedback by active galactic nuclei (AGNs). Provided some physics for the absolute normalization, the creation of the scaling relations can be fully explained by the hierarchical assembly of BH and stellar mass through galaxy merging, from an initially uncorrelated distribution of BH and stellar masses in the early universe. We show this with a suite of dark matter halo merger trees for which we make assumptions about (uncorrelated) BH and stellar mass values at early cosmic times. We then follow the halos in the presence of global star formation and BH accretion recipes that (1) work without any coupling of the two properties per individual galaxy and (2) correctly reproduce the observed star formation and BH accretion rate density in the universe. With disk-to-bulge conversion in mergers included, our simulations even create the observed slope of {approx}1.1 for the M{sub BH}-M{sub bulge} relation at z = 0. This also implies that AGN feedback is not a required (though still a possible) ingredient in galaxy evolution. In light of this, other mechanisms that can be invoked to truncate star formation in massive galaxies are equally justified.

  7. A Causal Relation between Bioluminescence and Oxygen to Quantify the Cell Niche

    PubMed Central

    Lambrechts, Dennis; Roeffaers, Maarten; Goossens, Karel; Hofkens, Johan; Van de Putte, Tom; Schrooten, Jan; Van Oosterwyck, Hans

    2014-01-01

    Bioluminescence imaging assays have become a widely integrated technique to quantify effectiveness of cell-based therapies by monitoring fate and survival of transplanted cells. To date these assays are still largely qualitative and often erroneous due to the complexity and dynamics of local micro-environments (niches) in which the cells reside. Here, we report, using a combined experimental and computational approach, on oxygen that besides being a critical niche component responsible for cellular energy metabolism and cell-fate commitment, also serves a primary role in regulating bioluminescent light kinetics. We demonstrate the potential of an oxygen dependent Michaelis-Menten relation in quantifying intrinsic bioluminescence intensities by resolving cell-associated oxygen gradients from bioluminescent light that is emitted from three-dimensional (3D) cell-seeded hydrogels. Furthermore, the experimental and computational data indicate a strong causal relation of oxygen concentration with emitted bioluminescence intensities. Altogether our approach demonstrates the importance of oxygen to evolve towards quantitative bioluminescence and holds great potential for future microscale measurement of oxygen tension in an easily accessible manner. PMID:24840204

  8. Causal Judgments of Positive Mood in Relation to Self-Regulation: A Case Study with Flemish Students

    ERIC Educational Resources Information Center

    Human-Vogel, Salome; van Petegem, Peter

    2008-01-01

    To examine students' causal judgements of positive mood in relation to self-regulation, 128 participants from two different schools representing two distinct educational environments (Technical/Vocational School (TSO/BSO): N = 63; General Secondary School (ASO): N = 65) were asked to judge 45 statements containing three possible relationships (A…

  9. Causal Factors and Adverse Events of Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

    NASA Technical Reports Server (NTRS)

    Reveley, Mary S.; Briggs, Jeffrey L.; Evans, Joni K.; Jones, Sharon M.; Kurtoglu, Tolga; Leone, Karen M.; Sandifer, Carl E.

    2011-01-01

    Causal factors in aviation accidents and incidents related to system/component failure/malfunction (SCFM) were examined for Federal Aviation Regulation Parts 121 and 135 operations to establish future requirements for the NASA Aviation Safety Program s Integrated Vehicle Health Management (IVHM) Project. Data analyzed includes National Transportation Safety Board (NSTB) accident data (1988 to 2003), Federal Aviation Administration (FAA) incident data (1988 to 2003), and Aviation Safety Reporting System (ASRS) incident data (1993 to 2008). Failure modes and effects analyses were examined to identify possible modes of SCFM. A table of potential adverse conditions was developed to help evaluate IVHM research technologies. Tables present details of specific SCFM for the incidents and accidents. Of the 370 NTSB accidents affected by SCFM, 48 percent involved the engine or fuel system, and 31 percent involved landing gear or hydraulic failure and malfunctions. A total of 35 percent of all SCFM accidents were caused by improper maintenance. Of the 7732 FAA database incidents affected by SCFM, 33 percent involved landing gear or hydraulics, and 33 percent involved the engine and fuel system. The most frequent SCFM found in ASRS were turbine engine, pressurization system, hydraulic main system, flight management system/flight management computer, and engine. Because the IVHM Project does not address maintenance issues, and landing gear and hydraulic systems accidents are usually not fatal, the focus of research should be those SCFMs that occur in the engine/fuel and flight control/structures systems as well as power systems.

  10. The Causal Effects of Relational Security and Insecurity on Condom Use Attitudes and Acquisition Behavior.

    PubMed

    Sakaluk, John Kitchener; Gillath, Omri

    2016-02-01

    Research on attachment and condom use has been limited to correlational studies of self-report measures, yielding inconsistent results. Here, we examined the causal effects of attachment priming on self-reported condom use attitudes and an observational measure of condom acquisition behavior. In three experiments, participants were exposed to one of three attachment primes (security, anxiety, or avoidance) or a control prime. For Study 1, participants in the security and anxiety conditions preferred condom non-use to a greater extent, compared to participants in the avoidance condition. This effect was replicated in Study 2, and was mediated by perceptions of sexual health threat. In Study 3, the effect of security priming on condom acquisition behavior was eliminated through the use of a framing manipulation, though the effect of primed attachment on condom use attitudes was not significant. A meta-analysis, however, revealed that the predicted effects of attachment priming were consistent across the three studies, supporting the role of attachment in evaluations of condom use. Priming attachment security or anxiety leads participants to perceive their sexual partners as less of a sexual health threat, resulting in a devaluation of condom use. Primed security also reduced condom acquisition behavior, though this negative effect eliminated by framing condoms as protecting a partner's sexual health. Overall, these studies suggest that relational factors, such as attachment, require greater consideration when studying sexual health and designing interventions. PMID:26566898

  11. Device-independent test of causal order and relations to fixed-points

    NASA Astrophysics Data System (ADS)

    Baumeler, Ämin; Wolf, Stefan

    2016-03-01

    Bell non-local correlations cannot be naturally explained in a fixed causal structure. This serves as a motivation for considering models where no global assumption is made beyond logical consistency. The assumption of a fixed causal order between a set of parties, together with free randomness, implies device-independent inequalities—just as the assumption of locality does. It is known that local validity of quantum theory is consistent with violating such inequalities. Moreover, for three parties or more, even the (stronger) assumption of local classical probability theory plus logical consistency allows for violating causal inequalities. Here, we show that a classical environment (with which the parties interact), possibly containing loops, is logically consistent if and only if whatever the involved parties do, there is exactly one fixed-point, the latter being representable as a mixture of deterministic fixed-points. We further show that the non-causal view allows for a model of computation strictly more powerful than computation in a world of fixed causal orders.

  12. Do people reason rationally about causally related events? Markov violations, weak inferences, and failures of explaining away.

    PubMed

    Rottman, Benjamin M; Hastie, Reid

    2016-06-01

    Making judgments by relying on beliefs about the causal relationships between events is a fundamental capacity of everyday cognition. In the last decade, Causal Bayesian Networks have been proposed as a framework for modeling causal reasoning. Two experiments were conducted to provide comprehensive data sets with which to evaluate a variety of different types of judgments in comparison to the standard Bayesian networks calculations. Participants were introduced to a fictional system of three events and observed a set of learning trials that instantiated the multivariate distribution relating the three variables. We tested inferences on chains X1→Y→X2, common cause structures X1←Y→X2, and common effect structures X1→Y←X2, on binary and numerical variables, and with high and intermediate causal strengths. We tested transitive inferences, inferences when one variable is irrelevant because it is blocked by an intervening variable (Markov Assumption), inferences from two variables to a middle variable, and inferences about the presence of one cause when the alternative cause was known to have occurred (the normative "explaining away" pattern). Compared to the normative account, in general, when the judgments should change, they change in the normative direction. However, we also discuss a few persistent violations of the standard normative model. In addition, we evaluate the relative success of 12 theoretical explanations for these deviations. PMID:27261539

  13. Using Fluctuation Analysis to Establish Causal Relations between Cellular Events without Experimental Perturbation

    PubMed Central

    Welf, Erik S.; Danuser, Gaudenz

    2014-01-01

    Experimental perturbations are commonly used to establish causal relationships between the molecular components of a pathway and their cellular functions; however, this approach suffers inherent limitations. Especially in pathways with a significant level of nonlinearity and redundancy among components, such perturbations induce compensatory responses that obscure the actual function of the targeted component in the unperturbed pathway. A complementary approach uses constitutive fluctuations in component activities to identify the hierarchy of information flow through pathways. Here, we review the motivation for using perturbation-free approaches and highlight recent advances made in using perturbation-free fluctuation analysis as a means to establish causality among cellular events. PMID:25468328

  14. Long-Range Temporal Correlations, Multifractality, and the Causal Relation between Neural Inputs and Movements

    PubMed Central

    Hu, Jing; Zheng, Yi; Gao, Jianbo

    2013-01-01

    Understanding the causal relation between neural inputs and movements is very important for the success of brain-machine interfaces (BMIs). In this study, we analyze 104 neurons’ firings using statistical, information theoretic, and fractal analysis. The latter include Fano factor analysis, multifractal adaptive fractal analysis (MF-AFA), and wavelet multifractal analysis. We find neuronal firings are highly non-stationary, and Fano factor analysis always indicates long-range correlations in neuronal firings, irrespective of whether those firings are correlated with movement trajectory or not, and thus does not reveal any actual correlations between neural inputs and movements. On the other hand, MF-AFA and wavelet multifractal analysis clearly indicate that when neuronal firings are not well correlated with movement trajectory, they do not have or only have weak temporal correlations. When neuronal firings are well correlated with movements, they are characterized by very strong temporal correlations, up to a time scale comparable to the average time between two successive reaching tasks. This suggests that neurons well correlated with hand trajectory experienced a “re-setting” effect at the start of each reaching task, in the sense that within the movement correlated neurons the spike trains’ long-range dependences persisted about the length of time the monkey used to switch between task executions. A new task execution re-sets their activity, making them only weakly correlated with their prior activities on longer time scales. We further discuss the significance of the coalition of those important neurons in executing cortical control of prostheses. PMID:24130549

  15. Long-Range Temporal Correlations, Multifractality, and the Causal Relation between Neural Inputs and Movements.

    PubMed

    Hu, Jing; Zheng, Yi; Gao, Jianbo

    2013-01-01

    Understanding the causal relation between neural inputs and movements is very important for the success of brain-machine interfaces (BMIs). In this study, we analyze 104 neurons' firings using statistical, information theoretic, and fractal analysis. The latter include Fano factor analysis, multifractal adaptive fractal analysis (MF-AFA), and wavelet multifractal analysis. We find neuronal firings are highly non-stationary, and Fano factor analysis always indicates long-range correlations in neuronal firings, irrespective of whether those firings are correlated with movement trajectory or not, and thus does not reveal any actual correlations between neural inputs and movements. On the other hand, MF-AFA and wavelet multifractal analysis clearly indicate that when neuronal firings are not well correlated with movement trajectory, they do not have or only have weak temporal correlations. When neuronal firings are well correlated with movements, they are characterized by very strong temporal correlations, up to a time scale comparable to the average time between two successive reaching tasks. This suggests that neurons well correlated with hand trajectory experienced a "re-setting" effect at the start of each reaching task, in the sense that within the movement correlated neurons the spike trains' long-range dependences persisted about the length of time the monkey used to switch between task executions. A new task execution re-sets their activity, making them only weakly correlated with their prior activities on longer time scales. We further discuss the significance of the coalition of those important neurons in executing cortical control of prostheses. PMID:24130549

  16. Deciphering causal and statistical relations of molecular aberrations and gene expressions in NCI-60 cell lines

    PubMed Central

    2011-01-01

    Background Cancer cells harbor a large number of molecular alterations such as mutations, amplifications and deletions on DNA sequences and epigenetic changes on DNA methylations. These aberrations may dysregulate gene expressions, which in turn drive the malignancy of tumors. Deciphering the causal and statistical relations of molecular aberrations and gene expressions is critical for understanding the molecular mechanisms of clinical phenotypes. Results In this work, we proposed a computational method to reconstruct association modules containing driver aberrations, passenger mRNA or microRNA expressions, and putative regulators that mediate the effects from drivers to passengers. By applying the module-finding algorithm to the integrated datasets of NCI-60 cancer cell lines, we found that gene expressions were driven by diverse molecular aberrations including chromosomal segments' copy number variations, gene mutations and DNA methylations, microRNA expressions, and the expressions of transcription factors. In-silico validation indicated that passenger genes were enriched with the regulator binding motifs, functional categories or pathways where the drivers were involved, and co-citations with the driver/regulator genes. Moreover, 6 of 11 predicted MYB targets were down-regulated in an MYB-siRNA treated leukemia cell line. In addition, microRNA expressions were driven by distinct mechanisms from mRNA expressions. Conclusions The results provide rich mechanistic information regarding molecular aberrations and gene expressions in cancer genomes. This kind of integrative analysis will become an important tool for the diagnosis and treatment of cancer in the era of personalized medicine. PMID:22051105

  17. [Representation of relations between television watching and delinquency within the scope of causal analysis models].

    PubMed

    Scheungrab, M

    1990-01-01

    The subject of research coucerns causal relationships between variables of consuming home videos and television and different indicators of delinquency ("acceptance of social norms" (NORM-AK), "perceived risk of punishment" (DEL-RISK), "severity of negative consequences" (NEG-VAL), "acceptance of illegitimate means" (ILLEG-M)). Additionally, factors of influence external to media are taken into consideration which are connected with delinquency according to criminologic results, i.e. variables of communication and variables of the family life and the structure of the family. The model is tested by a sample of N = 305 male pupils of a Regensburg vocational school with methods analysing causality ("2-Stage-Least-Square" (2-SLS) and "Latent variables path analysis with partial least squares estimation" (LVPLS)). The 2-SLS-estimates largely confirm the causal relationships supposed in the model. The results are, three significantly positive indirect connections from the preference for violence of home videos to the main indicator of delinquency ILLEG-M (by way of the variables "consumption of home videos" put on the Index, NEG-VAL and DEL-RISK). The direct influence of the preference for violence on television on ILLEG-M is confirmed, whereas the direct path from the popularity of violent video films to ILLEG-M cannot be proved. The LVPLS-results essentially correspond to the relationship shown by 2-SLS; in addition the LVPLS-estimates also confirm direct causal relationships between the latent variables "consumption of violent video films" and "delinquency proneness". PMID:2132917

  18. Causal Relations and Their Effects on the Comprehension of Narrative Texts.

    ERIC Educational Resources Information Center

    Slater, Wayne H.

    A study examined three variables derived from earlier research on comprehension and recall of narrative text: time in short-term memory; causal connections allowed; and referential connections allowed. Subjects, 84 randomly selected fourth graders in three suburban public elementary schools, read 8 short texts that each contained 4 embedded goals,…

  19. Trauma-Related Altered States of Consciousness (TRASC) and Functional Impairment II: Perceived Causal Relationships in an Online Sample.

    PubMed

    Tzannidakis, Nicole C A; Frewen, Paul

    2015-01-01

    Research supports the existence of a dissociative subtype of posttraumatic stress disorder, although studies have not directly compared the perceived impact of dissociative versus nondissociative posttraumatic symptoms on social and occupational functioning. In addition, research is beginning to differentiate between posttraumatic distress associated with normal waking consciousness (NWC) and dissociative experiences of trauma-related altered states of consciousness (TRASC) along multiple phenomenological dimensions. The current study investigated perceived causal relationships between posttraumatic symptoms associated with NWC-distress and TRASC on the one hand and interpersonal and occupational functioning on the other. Although both TRASC and NWC-distress independently accounted for variance in self-reported interpersonal and occupational problems, perceived causal relationship results showed that individuals tended to attribute their social and work-related problems more strongly to NWC-distress than to TRASC. Future research directions are discussed. PMID:26308190

  20. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness, and Verbal Short-Term Memory in Reading Skills: A Review

    ERIC Educational Resources Information Center

    Melby-Lervag, Monica

    2012-01-01

    The acknowledgement that educational achievement is highly dependent on successful reading development has led to extensive research on its underlying factors. A strong argument has been made for a causal relationship between reading and phoneme awareness; similarly, causal relations have been suggested for reading with short-term memory and rhyme…

  1. The Impact of Relative Poverty on Norwegian Adolescents’ Subjective Health: A Causal Analysis with Propensity Score Matching

    PubMed Central

    Elstad, Jon Ivar; Pedersen, Axel West

    2012-01-01

    Studies have revealed that relative poverty is associated with ill health, but the interpretations of this correlation vary. This article asks whether relative poverty among Norwegian adolescents is causally related to poor subjective health, i.e., self-reported somatic and mental symptoms. Data consist of interview responses from a sample of adolescents (N = 510) and their parents, combined with register data on the family’s economic situation. Relatively poor adolescents had significantly worse subjective health than non-poor adolescents. Relatively poor adolescents also experienced many other social disadvantages, such as parental unemployment and parental ill health. Comparisons between the relatively poor and the non-poor adolescents, using propensity score matching, indicated a negative impact of relative poverty on the subjective health among those adolescents who lived in families with relatively few economic resources. The results suggest that there is a causal component in the association between relative poverty and the symptom burden of disadvantaged adolescents. Relative poverty is only one of many determinants of adolescents’ subjective health, but its role should be acknowledged when policies for promoting adolescent health are designed. PMID:23249858

  2. Causal networks or causal islands? The representation of mechanisms and the transitivity of causal judgment

    PubMed Central

    Johnson, Samuel G. B.; Ahn, Woo-kyoung

    2014-01-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we used causal transitivity—the inference given A causes B and B causes C that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links (Experiments 1–3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4–5). PMID:25556901

  3. Causal determination of acoustic group velocity and frequency derivative of attenuation with finite-bandwidth Kramers-Kronig relations

    NASA Astrophysics Data System (ADS)

    Mobley, Joel; Waters, Kendall R.; Miller, James G.

    2005-07-01

    Kramers-Kronig (KK) analyses of experimental data are complicated by the extrapolation problem, that is, how the unexamined spectral bands impact KK calculations. This work demonstrates the causal linkages in resonant-type data provided by acoustic KK relations for the group velocity (cg) and the derivative of the attenuation coefficient (α') (components of the derivative of the acoustic complex wave number) without extrapolation or unmeasured parameters. These relations provide stricter tests of causal consistency relative to previously established KK relations for the phase velocity (cp) and attenuation coefficient (α) (components of the undifferentiated acoustic wave number) due to their shape invariance with respect to subtraction constants. For both the group velocity and attenuation derivative, three forms of the relations are derived. These relations are equivalent for bandwidths covering the entire infinite spectrum, but differ when restricted to bandlimited spectra. Using experimental data from suspensions of elastic spheres in saline, the accuracy of finite-bandwidth KK predictions for cg and α' is demonstrated. Of the multiple methods, the most accurate were found to be those whose integrals were expressed only in terms of the phase velocity and attenuation coefficient themselves, requiring no differentiated quantities.

  4. Is Abuse Causally Related to Urologic Symptoms? Results from the Boston Area Community Heath (BACH) Survey

    PubMed Central

    Link, Carol L.; Lutfey, Karen E.; Steers, William D.; McKinlay, John B.

    2007-01-01

    Objectives: We investigated (1) whether sexual, physical, or emotional abuse experienced either as a child or as an adolescent/adult is associated with symptoms of urinary frequency, urgency, and nocturia, and (2) the extent to which the observed association between abuse and urologic symptoms may be causal. Methods: Analyses are based on data from the Boston Area Community Health (BACH) survey, a community-based epidemiologic study of many different urologic symptoms and risk factors. BACH used a multistage stratified cluster sample to recruit 5506 adults, aged 30[en]79 yr (2301 men, 3205 women; 1770 black [African American], 1877 Hispanic, and 1859 white respondents). Results: The symptoms considered are common, with 33% of BACH respondents reporting urinary frequency, 12% reporting urgency, and 28% reporting nocturia. All three symptoms are positively associated with childhood and adolescent/adult sexual, physical, and emotional abuse (p < 0.05), with abuse significantly increasing the odds of urinary frequency by a factor ranging from 1.6 to 1.9, the odds of urgency by a factor from 2.0 to 2.3, and the odds of nocturia by a factor from 1.3 to 1.5. Conclusions: Our analyses extend previous work. First, we show a strong association between abuse and urinary frequency, urgency, and nocturia in a community-based random sample. Second, we move beyond discussion of statistical association and find considerable evidence to suggest that the relationship between abuse and these symptoms may be causal. PMID:17383083

  5. Increased Causal Connectivity Related to Anatomical Alterations as Potential Endophenotypes for Schizophrenia

    PubMed Central

    Guo, Wenbin; Liu, Feng; Xiao, Changqing; Yu, Miaoyu; Zhang, Zhikun; Liu, Jianrong; Zhang, Jian; Zhao, Jingping

    2015-01-01

    Abstract Anatomical and functional abnormalities in the cortico-cerebellar-thalamo-cortical circuit have been observed in schizophrenia patients and their unaffected siblings. However, it remains unclear to the relationship between anatomical and functional abnormalities within this circuit in schizophrenia patients and their unaffected siblings, which may serve as potential endophenotypes for schizophrenia. Anatomical and resting-state functional magnetic resonance imaging data were acquired from 49 first-episode, drug-naive schizophrenia patients, 46 unaffected siblings, and 46 healthy controls. Data were analyzed by using voxel-based morphometry and Granger causality analysis. The patients and the siblings shared anatomical deficits in the left middle temporal gyrus (MTG) and increased left MTG–left angular gyrus (AG) connectivity. Moreover, the left MTG–left AG connectivity negatively correlates to the duration of untreated psychosis in the patients. The findings indicate that anatomical deficits in the left MTG and its increased causal connectivity with the left AG may serve as potential endophenotypes for schizophrenia with clinical implications. PMID:26496253

  6. The development of causal categorization.

    PubMed

    Hayes, Brett K; Rehder, Bob

    2012-08-01

    Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children's classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults. PMID:22462547

  7. Circadian Rhythms and Mood Disorders: Are the Phenomena and Mechanisms Causally Related?

    PubMed

    Bechtel, William

    2015-01-01

    This paper reviews some of the compelling evidence of disrupted circadian rhythms in individuals with mood disorders (major depressive disorder, seasonal affective disorder, and bipolar disorder) and that treatments such as bright light, designed to alter circadian rhythms, are effective in treating these disorders. Neurotransmitters in brain regions implicated in mood regulation exhibit circadian rhythms. A mouse model originally employed to identify a circadian gene has proven a potent model for mania. While this evidence is suggestive of an etiological role for altered circadian rhythms in mood disorders, it is compatible with other explanations, including that disrupted circadian rhythms and mood disorders are effects of a common cause and that genes and proteins implicated in both simply have pleiotropic effects. In light of this, the paper advances a proposal as to what evidence would be needed to establish a direct causal link between disruption of circadian rhythms and mood disorders. PMID:26379559

  8. Inferring causality from relational data and designs: historical and contemporary lessons for research and clinical practice.

    PubMed

    Reynolds, C R

    1999-11-01

    My address to you today is born of frustration with the growing claims, evident in the research literature and in clinical reports that happen to cross my desk, of causation made on the basis of correlational data. I recall, as a sophomore in college, being taught early in my first experimental psychology course, "you cannot infer causality from correlation." This point was made adamant in my first face-to-face critique of an experimental psychology research paper by Dr. Robert T. Brown, who pointed out, in lowering my grade, that I had inferred organic causes to behavior patterns in gerbils based solely on correlational data. This caution was reiterated in my statistics courses until it must have been indelibly stamped upon my then still somewhat plastic brain. PMID:10806450

  9. Significant increase in trisomy 21 in Berlin nine months after the Chernobyl reactor accident: temporal correlation or causal relation?

    PubMed Central

    Sperling, K.; Pelz, J.; Wegner, R. D.; Dörries, A.; Grüters, A.; Mikkelsen, M.

    1994-01-01

    OBJECTIVE--To assess whether the increased prevalence of trisomy 21 in West Berlin in January 1987 might have been causally related to exposure to ionising radiation as a result of the Chernobyl reactor accident or was merely a chance event. DESIGN--Analysis of monthly prevalence of trisomy 21 in West Berlin from January 1980 to December 1989. SETTING--Confines of West Berlin. RESULTS--Owing to the former "island" situation of West Berlin and its well organised health services, ascertainment of trisomy 21 was thought to be almost complete. A cluster of 12 cases occurred in January 1987 as compared with two or three expected. After exclusion of factors that might have explained the increase, including maternal age distribution, only exposure to radiation as a result of the Chernobyl reactor accident remained. In six of seven cases that could be studied cytogenetically the extra chromosome was of maternal origin, confirming that nondisjunction had occurred at about the time of conception. CONCLUSION--On the basis of two assumptions--(a) that maternal meiosis is an error prone process susceptible to exogenous factors at the time of conception; (b) that owing to the high prevalence of iodine deficiency in Berlin a large amount of iodine-131 would have been accumulated over a short period--it is concluded that the increased prevalence of trisomy 21 in West Berlin in January 1987 was causally related to a short period of exposure to ionising radiation as a result of the Chernobyl reactor accident. PMID:8044094

  10. Causal Analysis After Haavelmo

    PubMed Central

    Heckman, James; Pinto, Rodrigo

    2014-01-01

    Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123

  11. Causal Factors and Adverse Conditions of Aviation Accidents and Incidents Related to Integrated Resilient Aircraft Control

    NASA Technical Reports Server (NTRS)

    Reveley, Mary S.; Briggs, Jeffrey L.; Evans, Joni K.; Sandifer, Carl E.; Jones, Sharon Monica

    2010-01-01

    The causal factors of accidents from the National Transportation Safety Board (NTSB) database and incidents from the Federal Aviation Administration (FAA) database associated with loss of control (LOC) were examined for four types of operations (i.e., Federal Aviation Regulation Part 121, Part 135 Scheduled, Part 135 Nonscheduled, and Part 91) for the years 1988 to 2004. In-flight LOC is a serious aviation problem. Well over half of the LOC accidents included at least one fatality (80 percent in Part 121), and roughly half of all aviation fatalities in the studied time period occurred in conjunction with LOC. An adverse events table was updated to provide focus to the technology validation strategy of the Integrated Resilient Aircraft Control (IRAC) Project. The table contains three types of adverse conditions: failure, damage, and upset. Thirteen different adverse condition subtypes were gleaned from the Aviation Safety Reporting System (ASRS), the FAA Accident and Incident database, and the NTSB database. The severity and frequency of the damage conditions, initial test conditions, and milestones references are also provided.

  12. Is Socioeconomic Status of the Rearing Environment Causally Related to Obesity in the Offspring?

    PubMed Central

    Fontaine, Kevin R.; Robertson, Henry T.; Holst, Claus; Desmond, Renee; Stunkard, Albert J.; Sørensen, Thorkild I. A.; Allison, David B.

    2011-01-01

    We attempt to elucidate whether there might be a causal connection between the socioeconomic status (SES) of the rearing environment and obesity in the offspring using data from two large-scale adoption studies: (1) The Copenhagen Adoption Study of Obesity (CASO), and (2) The Survey of Holt Adoptees and Their Families (HOLT). In CASO, the SES of both biological and adoptive parents was known, but all children were adopted. In HOLT, only the SES of the rearing parents was known, but the children could be either biological or adopted. After controlling for relevant covariates (e.g., adoptee age at measurement, adoptee age at transfer, adoptee sex) the raw (unstandardized) regression coefficients for adoptive and biological paternal SES on adoptee body mass index (BMI: kg/m2) in CASO were -.22 and -.23, respectively, both statistically significant (p = 0.01). Controlling for parental BMI (both adoptive and biological) reduced the coefficient for biological paternal SES by 44% (p = .034) and the coefficient for adoptive paternal SES by 1%. For HOLT, the regression coefficients for rearing parent SES were -.42 and -.25 for biological and adoptive children, respectively. Controlling for the average BMI of the rearing father and mother (i.e., mid-parental BMI) reduced the SES coefficient by 47% in their biological offspring (p≤.0001), and by 12% in their adoptive offspring (p = .09). Thus, despite the differing structures of the two adoption studies, both suggest that shared genetic diathesis and direct environmental transmission contribute about equally to the association between rearing SES and offspring BMI. PMID:22110724

  13. Is There a Causal Relation between Maternal Acetaminophen Administration and ADHD?

    PubMed Central

    Saad, Antonio; Hegde, Shruti; Kechichian, Talar; Gamble, Phyllis; Rahman, Mahbubur; Stutz, Sonja J.; Anastasio, Noelle C.; Alshehri, Wael; Lei, Jun; Mori, Susumu; Kajs, Bridget; Cunningham, Kathryn A.; Saade, George; Burd, Irina; Costantine, Maged

    2016-01-01

    Objective Recent epidemiological studies reported an association between maternal intake of acetaminophen (APAP) and attention deficit hyperactivity disorder (ADHD) in their children. However, none of these studies demonstrated causality. Our objective was to determine whether exposure to APAP during pregnancy result in hyperkinetic dysfunctions in offspring, using a murine model. Material and Methods Pregnant CD1 mice (N = 8/group) were allocated to receive by gavage either APAP (150 mg/kg/day, equivalent to the FDA-approved maximum human clinical dose), or 0.5% carboxymethylcellulose (control group), starting on embryonic day 7 until delivery. Maternal serum APAP and alanine transaminase (ALT) concentrations were determined by ELISA and kinetic colorimetric assays, respectively. Open field locomotor activity (LMA) in the 30-day old mouse offspring was quantified using Photobeam Activity System. Mouse offspring were then sacrificed, whole brains processed for magnetic resonance imaging (MRI; 11.7 Tesla magnet) and for neuronal quantification using Nissl stain. The association between APAP exposure and LMA in mouse offspring was analyzed using a mixed effects Poisson regression model that accounted for mouse offspring weight, gender, random selection, and testing time and day. We corrected for multiple comparisons and considered P<0.008 as statistically significant. Results Maternal serum APAP concentration peaked 30 minutes after gavage, reaching the expected mean of 117 μg/ml. Serum ALT concentrations were not different between groups. There were no significant differences in vertical (rearing), horizontal, or total locomotor activity between the two rodent offspring groups at the P level fixed to adjust for multiple testing. In addition, no differences were found in volumes of 29 brain areas of interest on MRI or in neuronal quantifications between the two groups. Conclusion This study refutes that hypothesis that prenatal exposure to APAP causes hyperkinetic

  14. An application of GIS and Bayesian network in studying spatial-causal relations between enterprises and environmental factors

    NASA Astrophysics Data System (ADS)

    Shen, Tiyan; Li, Xi; Li, Maiqing

    2009-10-01

    The paper intends to employ Geographic Information System (GIS) and Bayesian Network to discover the spatial causality between enterprises and environmental factors in Beijing Metropolis. The census data of Beijing was spatialized by means of GIS in the beginning, and then the training data was made using density mapping technique. Base on the training data, the structure of a Bayesian Network was learnt with the help of Maximum Weight Spanning Tree. Eight direct relations were discussed in the end, of which, the most exciting discovery, "Enterprise-Run Society", as the symbol of the former planned economy, was emphasized in the spatial relations between heavy industry and schools. Though the final result is not so creative in economic perspective, it is of significance in technique view due to all discoveries were drawn from data, therefore leading to the realization of the importance of GIS and data mining to economic geography research.

  15. Warp drive and causality

    NASA Astrophysics Data System (ADS)

    Everett, Allen E.

    1996-06-01

    Alcubierre recently exhibited a spacetime which, within the framework of general relativity, allows travel at superluminal speeds if matter with a negative energy density can exist, and conjectured that it should be possible to use similar techniques to construct a theory containing closed causal loops and, thus, travel backwards in time. We verify this conjecture by exhibiting a simple modification of Alcubierre's model, requiring no additional assumptions, in which causal loops are possible. We also note that this mechanism for generating causal loops differs in essential ways from that discovered by Gott involving cosmic strings.

  16. Epidemiological causality.

    PubMed

    Morabia, Alfredo

    2005-01-01

    Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population. PMID:16898206

  17. Anterior Cingulate Cortico-Hippocampal Dysconnectivity in Unaffected Relatives of Schizophrenia Patients: A Stochastic Dynamic Causal Modeling Study.

    PubMed

    Xi, Yi-Bin; Li, Chen; Cui, Long-Biao; Liu, Jian; Guo, Fan; Li, Liang; Liu, Ting-Ting; Liu, Kang; Chen, Gang; Xi, Min; Wang, Hua-Ning; Yin, Hong

    2016-01-01

    Familial risk plays a significant role in the etiology of schizophrenia (SZ). Many studies using neuroimaging have demonstrated structural and functional alterations in relatives of SZ patients, with significant results found in diverse brain regions involving the anterior cingulate cortex (ACC), caudate, dorsolateral prefrontal cortex (DLPFC), and hippocampus. This study investigated whether unaffected relatives of first episode SZ differ from healthy controls (HCs) in effective connectivity measures among these regions. Forty-six unaffected first-degree relatives of first episode SZ patients-according to the DSM-IV-were studied. Fifty HCs were included for comparison. All subjects underwent resting state functional magnetic resonance imaging (fMRI). We used stochastic dynamic causal modeling (sDCM) to estimate the directed connections between the left ACC, right ACC, left caudate, right caudate, left DLPFC, left hippocampus, and right hippocampus. We used Bayesian parameter averaging (BPA) to characterize the differences. The BPA results showed hyperconnectivity from the left ACC to right hippocampus and hypoconnectivity from the right ACC to right hippocampus in SZ relatives compared to HCs. The pattern of anterior cingulate cortico-hippocampal connectivity in SZ relatives may be a familial feature of SZ risk, appearing to reflect familial susceptibility for SZ. PMID:27512370

  18. Anterior Cingulate Cortico-Hippocampal Dysconnectivity in Unaffected Relatives of Schizophrenia Patients: A Stochastic Dynamic Causal Modeling Study

    PubMed Central

    Xi, Yi-Bin; Li, Chen; Cui, Long-Biao; Liu, Jian; Guo, Fan; Li, Liang; Liu, Ting-Ting; Liu, Kang; Chen, Gang; Xi, Min; Wang, Hua-Ning; Yin, Hong

    2016-01-01

    Familial risk plays a significant role in the etiology of schizophrenia (SZ). Many studies using neuroimaging have demonstrated structural and functional alterations in relatives of SZ patients, with significant results found in diverse brain regions involving the anterior cingulate cortex (ACC), caudate, dorsolateral prefrontal cortex (DLPFC), and hippocampus. This study investigated whether unaffected relatives of first episode SZ differ from healthy controls (HCs) in effective connectivity measures among these regions. Forty-six unaffected first-degree relatives of first episode SZ patients—according to the DSM-IV—were studied. Fifty HCs were included for comparison. All subjects underwent resting state functional magnetic resonance imaging (fMRI). We used stochastic dynamic causal modeling (sDCM) to estimate the directed connections between the left ACC, right ACC, left caudate, right caudate, left DLPFC, left hippocampus, and right hippocampus. We used Bayesian parameter averaging (BPA) to characterize the differences. The BPA results showed hyperconnectivity from the left ACC to right hippocampus and hypoconnectivity from the right ACC to right hippocampus in SZ relatives compared to HCs. The pattern of anterior cingulate cortico-hippocampal connectivity in SZ relatives may be a familial feature of SZ risk, appearing to reflect familial susceptibility for SZ. PMID:27512370

  19. Public Relations Roles and Systems Theory: Functional and Historicist Causal Models.

    ERIC Educational Resources Information Center

    Broom, Glen M.

    The effectiveness of an organizations's adaptive behavior depends on the extent to which public relations concerns are considered in goal setting and program planning. The following five open systems propositions, based on a "functional" paradigm, address the complex relationship between public relations and organizational intelligence and do not…

  20. PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.

    PubMed

    Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

    2013-01-01

    One of the most common and challenging problem in biomedical text mining is to mine protein-protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder--a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. DATABASE URL: http://www.biomining-bu.in/ppinterfinder/ PMID:23325628

  1. Dynamics of large-scale cortical interactions at high gamma frequencies during word production: Event related causality (ERC) analysis of human electrocorticography (ECoG)

    PubMed Central

    Korzeniewska, Anna; Franaszczuk, Piotr J.; Crainiceanu, Ciprian M.; Kuś, Rafał; Crone, Nathan E.

    2011-01-01

    Intracranial EEG studies in humans have shown that functional brain activation in a variety of functional-anatomic domains of human cortex is associated with an increase in power at a broad range of high gamma (> 60 Hz) frequencies. Although these electrophysiological responses are highly specific for the location and timing of cortical processing and in animal recordings are highly correlated with increased population firing rates, there has been little direct empirical evidence for causal interactions between different recording sites at high gamma frequencies. Such causal interactions are hypothesized to occur during cognitive tasks that activate multiple brain regions. To determine whether such causal interactions occur at high gamma frequencies and to investigate their functional significance, we used event-related causality (ERC) analysis to estimate the dynamics, directionality, and magnitude of event-related causal interactions using subdural electrocorticography (ECoG) recorded during two word production tasks: picture naming and auditory word repetition. A clinical subject who had normal hearing but was skilled in American Signed Language (ASL) provided a unique opportunity to test our hypothesis with reference to a predictable pattern of causal interactions, i.e. that language cortex interacts with different areas of sensorimotor cortex during spoken vs. signed responses. Our ERC analyses confirmed this prediction. During word production with spoken responses, perisylvian language sites had prominent causal interactions with mouth/tongue areas of motor cortex, and when responses were gestured in sign language, the most prominent interactions involved hand and arm areas of motor cortex. Furthermore, we found that the sites from which the most numerous and prominent causal interactions originated, i.e. sites with a pattern of ERC “divergence”, were also sites where high gamma power increases were most prominent and where electrocortical stimulation

  2. A Cross National Study of the Relative Influence of School Education: A Causal Analysis.

    ERIC Educational Resources Information Center

    Langton, Kenneth P.; Karns, David A.

    This study examines, within a single model, the relative influence of family, school, and work group participation upon different levels of political efficacy and participation within a developmental context. The study is a preliminary analysis because only data for the U.S.A., Great Britain, Germany, Italy, and Mexico were obtainable.…

  3. Mitochondrial-derived reactive oxygen species (ROS) play a causal role in aging-related intervertebral disc degeneration

    PubMed Central

    Nasto, Luigi A.; Robinson, Andria R.; Ngo, Kevin; Clauson, Cheryl L.; Dong, Qing; St. Croix, Claudette; Sowa, Gwendolyn; Pola, Enrico; Robbins, Paul D.; Kang, James; Niedernhofer, Laura J.; Wipf, Peter; Vo, Nam V.

    2013-01-01

    Oxidative damage is a well-established driver of aging. Evidence of oxidative stress exists in aged and degenerated discs, but it is unclear how it affects disc metabolism. In this study, we first determined whether oxidative stress negatively impacts disc matrix metabolism using disc organotypic and cell cultures. Mouse disc organotypic culture grown at atmospheric oxygen (20% O2) exhibited perturbed disc matrix homeostasis, including reduced proteoglycan synthesis and enhanced expression of matrix metalloproteinases, compared to discs grown at low oxygen levels (5% O2). Human disc cells grown at 20% O2 showed increased levels of mitochondrial-derived superoxide anions and perturbed matrix homeostasis. Treatment of disc cells with the mitochondria-targeted reactive oxygen species (ROS) scavenger XJB-5-131 blunted the adverse effects caused by 20% O2. Importantly, we demonstrated that treatment of accelerated aging Ercc1−/Δmice, previously established to be a useful in vivo model to study age-related intervertebral disc degeneration (IDD), also resulted in improved disc total glycosaminoglycan content and proteoglycan synthesis. This demonstrates that mitochondrial-derived ROS contributes to age-associated IDD in Ercc1−/Δmice. Collectively, these data provide strong experimental evidence that mitochondrial-derived ROS play a causal role in driving changes linked to aging-related IDD and a potentially important role for radical scavengers in preventing IDD. PMID:23389888

  4. Causal inference based on counterfactuals

    PubMed Central

    Höfler, M

    2005-01-01

    Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept. PMID:16159397

  5. Human factors identification and classification related to accidents'causality on hand injuries in the manufacturing industry.

    PubMed

    Reyes-Martínez, Rosa María; Maldonado-Macías, Aide; Prado-León, Lilia Roselia

    2012-01-01

    The causes of occupational accidents from the perspective of human factors have been a subject which has received little attention into the field of scientific research. The aim of this research was to identify and classify the human factors that influence human errors and failures that cause accidents and injuries specifically on hands. Available studies related to the topic have been developed mainly for aerospace applications and are found insufficient to explain accidents causalities in the manufacturing industry. This research was developed in the assembly industry of automotive harnesses and was conducted following a mixed Cognitive Anthropological approach. This study was developed in two phases. During the first qualitative phase, participants freely listed their knowledge to identify elements of the cultural domain, then and in the second phase they performed the successive pile sort technique for the collection data to classify elements in the cultural domain. Statistical models like Cluster Analysis and Multidimensional Scaling were applied for results' validation purposes. As results, 70 different human factors were identified and in the second phase they were classified into 4 main categories which were: human error, unsafe conditions, individual factors, and organizational factors. Statistical methods validated these results. PMID:22317198

  6. The Development of Causal Categorization

    ERIC Educational Resources Information Center

    Hayes, Brett K.; Rehder, Bob

    2012-01-01

    Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs.…

  7. Loop Analysis of Causal Feedback in Epidemiology: An Illustration Relating To Urban Neighborhoods and Resident Depressive Experiences

    PubMed Central

    2008-01-01

    The causal feedback implied by urban neighborhood conditions that shape human health experiences, that in turn shape neighborhood conditions through a complex causal web, raises a challenge for traditional epidemiological causal analyses. This article introduces the loop analysis method, and builds off of a core loop model linking neighborhood property vacancy rate, resident depressive symptoms, rate of neighborhood death, and rate of neighborhood exit in a feedback network. I justify and apply loop analysis to the specific example of depressive symptoms and abandoned urban residential property to show how inquiries into the behavior of causal systems can answer different kinds of hypotheses, and thereby compliment those of causal modeling using statistical models. Neighborhood physical conditions that are only indirectly influenced by depressive symptoms may nevertheless manifest in the mental health experiences of their residents; conversely, neighborhood physical conditions may be a significant mental health risk for the population of neighborhood residents. I find that participatory greenspace programs are likely to produce adaptive responses in depressive symptoms and different neighborhood conditions, which are different in character to non-participatory greenspace interventions. PMID:17706851

  8. Ensemble of Causal Trees

    NASA Astrophysics Data System (ADS)

    Bialas, Piotr

    2003-10-01

    We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite.

  9. Sensing the Coherence of Biology in Contrast to Psychology: Young Children's Use of Causal Relations to Distinguish Two Foundational Domains

    ERIC Educational Resources Information Center

    Erickson, Jane E.; Keil, Frank C.; Lockhart, Kristi L.

    2010-01-01

    To what extent do children understand that biological processes fall into 1 coherent domain unified by distinct causal principles? In Experiments 1 and 2 (N = 125) kindergartners are given triads of biological and psychological processes and asked to identify which 2 members of the triad belong together. Results show that 5-year-olds correctly…

  10. A Storybook Method for Exploring Young Children's Views of Illness Causality in Relation to the Familial Context

    ERIC Educational Resources Information Center

    McIntosh, Caroline; Stephens, Christine

    2012-01-01

    In this paper we describe a method for exploring young children's views of illness causality in social context. Studies of children's conceptualisation of illness have predominantly focused on the nature of children's knowledge rather than locating that knowledge within socio-cultural contexts. Adopting a socio-constructivist perspective we sought…

  11. Do people agree about the causes of behavior? A social relations analysis of behavior ratings and causal attributions.

    PubMed

    Robins, Richard W; Mendelsohn, Gerald A; Connell, Joanie B; Kwan, Virginia S Y

    2004-02-01

    Two studies examined consistency and agreement in behavior ratings and causal attributions. In Study 1, participants (N = 280) engaged in a series of getting-acquainted conversations in one of 3 communication media (face-to-face, telephone, computer mediated); in Study 2, participants (N = 120) engaged in a competitive group task. In both studies, participants rated themselves and their interaction partners on a set of behaviors and then made attributions about the causes of those behaviors. The major findings were that (a) participants consistently favored some causal factors over others in explaining both their own and their partners' behavior, supporting the existence of generalized attributional styles; and (b) participants showed moderate self-partner and partner-partner agreement about behavior but virtually no agreement about the causes of behavior. Thus, in brief interactions people tend to see themselves and others through the lens of their stable patterns of perceiving and interpreting behavior. PMID:14769088

  12. On causality of extreme events

    PubMed Central

    2016-01-01

    Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available. PMID:27330866

  13. Causal essentialism in kinds.

    PubMed

    Ahn, Woo-kyoung; Taylor, Eric G; Kato, Daniel; Marsh, Jessecae K; Bloom, Paul

    2013-06-01

    The current study examines causal essentialism, derived from psychological essentialism of concepts. We examine whether people believe that members of a category share some underlying essence that is both necessary and sufficient for category membership and that also causes surface features. The main claim is that causal essentialism is restricted to categories that correspond to our intuitive notions of existing kinds and hence is more attenuated for categories that are based on arbitrary criteria. Experiments 1 and 3 found that people overtly endorse causal essences in nonarbitrary kinds but are less likely to do so for arbitrary categories. Experiments 2 and 4 found that people were more willing to generalize a member's known causal relations (or lack thereof) when dealing with a kind than when dealing with an arbitrary category. These differences between kinds and arbitrary categories were found across various domains-not only for categories of living things, but also for artefacts. These findings have certain real-world implications, including how people make sense of mental disorders that are treated as real kinds. PMID:23098315

  14. The Visual Causality Analyst: An Interactive Interface for Causal Reasoning.

    PubMed

    Wang, Jun; Mueller, Klaus

    2016-01-01

    Uncovering the causal relations that exist among variables in multivariate datasets is one of the ultimate goals in data analytics. Causation is related to correlation but correlation does not imply causation. While a number of casual discovery algorithms have been devised that eliminate spurious correlations from a network, there are no guarantees that all of the inferred causations are indeed true. Hence, bringing a domain expert into the casual reasoning loop can be of great benefit in identifying erroneous casual relationships suggested by the discovery algorithm. To address this need we present the Visual Causal Analyst-a novel visual causal reasoning framework that allows users to apply their expertise, verify and edit causal links, and collaborate with the causal discovery algorithm to identify a valid causal network. Its interface consists of both an interactive 2D graph view and a numerical presentation of salient statistical parameters, such as regression coefficients, p-values, and others. Both help users in gaining a good understanding of the landscape of causal structures particularly when the number of variables is large. Our framework is also novel in that it can handle both numerical and categorical variables within one unified model and return plausible results. We demonstrate its use via a set of case studies using multiple practical datasets. PMID:26529703

  15. Quantum causal modelling

    NASA Astrophysics Data System (ADS)

    Costa, Fabio; Shrapnel, Sally

    2016-06-01

    Causal modelling provides a powerful set of tools for identifying causal structure from observed correlations. It is well known that such techniques fail for quantum systems, unless one introduces ‘spooky’ hidden mechanisms. Whether one can produce a genuinely quantum framework in order to discover causal structure remains an open question. Here we introduce a new framework for quantum causal modelling that allows for the discovery of causal structure. We define quantum analogues for core features of classical causal modelling techniques, including the causal Markov condition and faithfulness. Based on the process matrix formalism, this framework naturally extends to generalised structures with indefinite causal order.

  16. Improving Causality Induction with Category Learning

    PubMed Central

    Wang, Zhihong; Shao, Zhiqing

    2014-01-01

    Causal relations are of fundamental importance for human perception and reasoning. According to the nature of causality, causality has explicit and implicit forms. In the case of explicit form, causal-effect relations exist at either clausal or discourse levels. The implicit causal-effect relations heavily rely on empirical analysis and evidence accumulation. This paper proposes a comprehensive causality extraction system (CL-CIS) integrated with the means of category-learning. CL-CIS considers cause-effect relations in both explicit and implicit forms and especially practices the relation between category and causality in computation. In elaborately designed experiments, CL-CIS is evaluated together with general causality analysis system (GCAS) and general causality analysis system with learning (GCAS-L), and it testified to its own capability and performance in construction of cause-effect relations. This paper confirms the expectation that the precision and coverage of causality induction can be remarkably improved by means of causal and category learning. PMID:24883419

  17. Cross-lagged relations between mentoring received from supervisors and employee OCBs: Disentangling causal direction and identifying boundary conditions.

    PubMed

    Eby, Lillian T; Butts, Marcus M; Hoffman, Brian J; Sauer, Julia B

    2015-07-01

    Although mentoring has documented relationships with employee attitudes and outcomes of interest to organizations, neither the causal direction nor boundary conditions of the relationship between mentoring and organizational citizenship behaviors (OCBs) has been fully explored. On the basis of Social Learning Theory (SLT; Bandura, 1977, 1986), we predicted that mentoring received by supervisors would causally precede OCBs, rather than employee OCBs resulting in the receipt of more mentoring from supervisors. Results from cross-lagged data collected at 2 points in time from 190 intact supervisor-employee dyads supported our predictions; however, only for OCBs directed at individuals (OCB-Is) and not for OCBs directed at the organization (OCB-Os). Further supporting our theoretical rationale for expecting mentoring to precede OCBs, we found that coworker support operates as a substitute for mentoring in predicting OCB-Is. By contrast, no moderating effects were found for perceived organizational support. The results are discussed in terms of theoretical implications for mentoring and OCB research, as well as practical suggestions for enhancing employee citizenship behaviors. PMID:25602124

  18. Exposure to traffic-related air pollution during pregnancy and term low birth weight: estimation of causal associations in a semiparametric model.

    PubMed

    Padula, Amy M; Mortimer, Kathleen; Hubbard, Alan; Lurmann, Frederick; Jerrett, Michael; Tager, Ira B

    2012-11-01

    Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000-2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants. PMID:23045474

  19. Exposure to Traffic-related Air Pollution During Pregnancy and Term Low Birth Weight: Estimation of Causal Associations in a Semiparametric Model

    PubMed Central

    Padula, Amy M.; Mortimer, Kathleen; Hubbard, Alan; Lurmann, Frederick; Jerrett, Michael; Tager, Ira B.

    2012-01-01

    Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000–2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants. PMID:23045474

  20. The Power of Causal Beliefs and Conflicting Evidence on Causal Judgments and Decision Making

    ERIC Educational Resources Information Center

    Garcia-Retamero, Rocio; Muller, Stephanie M.; Catena, Andres; Maldonado, Antonio

    2009-01-01

    In two experiments, we investigated the relative impact of causal beliefs and empirical evidence on both decision making and causal judgments, and whether this relative impact could be altered by previous experience. 2. Selected groups of participants in both experiments received pre-training with either causal or neutral cues, or no pre-training…

  1. Attitudes toward Others Depend upon Self and Other Causal Uncertainty

    PubMed Central

    Tobin, Stephanie J.; Osika, Matylda M.; McLanders, Mia

    2014-01-01

    People who are high in causal uncertainty doubt their own ability to understand the causes of social events. In three studies, we examined the effects of target and perceiver causal uncertainty on attitudes toward the target. Target causal uncertainty was manipulated via responses on a causal uncertainty scale in Studies 1 and 2, and with a scenario in Study 3. In Studies 1 and 2, we found that participants liked the low causal uncertainty target more than the high causal uncertainty target. This preference was stronger for low relative to high causal uncertainty participants because high causal uncertainty participants held more uncertain ideals. In Study 3, we examined the value individuals place upon causal understanding (causal importance) as an additional moderator. We found that regardless of their own causal uncertainty level, participants who were high in causal importance liked the low causal uncertainty target more than the high causal uncertainty target. However, when participants were low in causal importance, low causal uncertainty perceivers showed no preference and high causal uncertainty perceivers preferred the high causal uncertainty target. These findings reveal that goal importance and ideals can influence how perceivers respond to causal uncertainty in others. PMID:24504048

  2. Quantifying causal coupling strength: A lag-specific measure for multivariate time series related to transfer entropy

    NASA Astrophysics Data System (ADS)

    Runge, Jakob; Heitzig, Jobst; Marwan, Norbert; Kurths, Jürgen

    2012-12-01

    While it is an important problem to identify the existence of causal associations between two components of a multivariate time series, a topic addressed in Runge, Heitzig, Petoukhov, and Kurths [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.108.258701 108, 258701 (2012)], it is even more important to assess the strength of their association in a meaningful way. In the present article we focus on the problem of defining a meaningful coupling strength using information-theoretic measures and demonstrate the shortcomings of the well-known mutual information and transfer entropy. Instead, we propose a certain time-delayed conditional mutual information, the momentary information transfer (MIT), as a lag-specific measure of association that is general, causal, reflects a well interpretable notion of coupling strength, and is practically computable. Rooted in information theory, MIT is general in that it does not assume a certain model class underlying the process that generates the time series. As discussed in a previous paper [Runge, Heitzig, Petoukhov, and Kurths, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.108.258701 108, 258701 (2012)], the general framework of graphical models makes MIT causal in that it gives a nonzero value only to lagged components that are not independent conditional on the remaining process. Further, graphical models admit a low-dimensional formulation of conditions, which is important for a reliable estimation of conditional mutual information and, thus, makes MIT practically computable. MIT is based on the fundamental concept of source entropy, which we utilize to yield a notion of coupling strength that is, compared to mutual information and transfer entropy, well interpretable in that, for many cases, it solely depends on the interaction of the two components at a certain lag. In particular, MIT is, thus, in many cases able to exclude the misleading influence of autodependency within a process in an information-theoretic way

  3. Use of a Mendelian randomization approach to assess the causal relation of gamma-Glutamyltransferase with blood pressure and serum insulin levels.

    PubMed

    Conen, David; Vollenweider, Peter; Rousson, Valentin; Marques-Vidal, Pedro; Paccaud, Fred; Waeber, Gérard; Bochud, Murielle

    2010-12-15

    Elevated levels of γ-glutamyltransferase (GGT) have been associated with elevated blood pressure (BP) and diabetes. However, the causality of these relations has not been addressed. The authors performed a cross-sectional analysis (2003-2006) among 4,360 participants from the population-based Cohorte Lausannoise (CoLaus) Study (Lausanne, Switzerland). The rs2017869 variant of the γ-glutamyltransferase 1 (GGT1) gene, which explained 1.6% of the variance in GGT levels, was used as an instrument for Mendelian randomization (MR). Sex-specific GGT quartiles were strongly associated with both systolic and diastolic BP (all P's < 0.0001). After multivariable adjustment, these relations were attenuated but remained significant. Using MR, the authors observed no positive association of GGT with BP (systolic: β -5.68, 95% confidence interval (CI): -11.51, 0.16 (P = 0.06); diastolic: β = -2.24, 95% CI: -5.98, 1.49 (P = 0.24)). The association of GGT with insulin was also attenuated after multivariable adjustment but persisted in the fully adjusted model (β = 0.07, 95% CI: 0.04, 0.09; P < 0.0001). Using MR, the authors also observed a positive association of GGT with insulin (β = 0.19, 95% CI: 0.01, 0.37; P = 0.04). In conclusion, the authors found evidence for a direct causal relation of GGT with fasting insulin but not with BP. PMID:21044991

  4. Cross-sectional schooling-health associations misrepresented causal schooling effects on adult health and health-related behaviors: evidence from the Chinese Adults Twins Survey.

    PubMed

    Behrman, Jere R; Xiong, Yanyan; Zhang, Junsen

    2015-02-01

    Adult health outcomes and health behaviors are often associated with schooling. However, such associations do not necessarily imply that schooling has causal effects on health with the signs or magnitudes found in the cross-sectional associations. Schooling may be proxying for unobserved factors related to genetics and family background that directly affect both health and schooling. Recently several studies have used within-monozygotic (MZ) twins methods to control for unobserved factors shared by identical twins. Within-MZ estimates for developed countries are generally smaller than suggested by cross-sectional associations, consistent with positive correlations between unobserved factors that determine schooling and those that determine health. This study contributes new estimates of cross-sectional associations and within-MZ causal effects using the Chinese Adults Twins Survey, the first study of its type for developing countries. The cross-sectional estimates suggest that schooling is significantly associated with adult health-related behaviors (smoking, drinking, exercising) but not with own or spouse health outcomes (general health, mental health, overweight, chronic diseases). However, within-MZ-twins estimators change the estimates for approximately half of these health indicators, in one case declining in absolute magnitudes and becoming insignificant and in the other cases increasing in absolute magnitudes. Within-MZ estimates indicate significant pro-health effects for at least one of the indicators for own health (better mental health), own health-related behaviors (less smoking) and spouse health (less overweight). PMID:25464872

  5. Causal Inference in Public Health

    PubMed Central

    Glass, Thomas A.; Goodman, Steven N.; Hernán, Miguel A.; Samet, Jonathan M.

    2014-01-01

    Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action’s consequences rather than the less precise notion of a risk factor’s causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world. PMID:23297653

  6. [Causality in occupational health: the Ardystil case].

    PubMed

    García García, A M; Benavides, F G

    1995-01-01

    Establishing causal relationships has been and is today a matter of debate in epidemiology. The observational nature of epidemiological research rends difficult the proving of these relationships. Related to this, different models and causal criteria have been proposed in order to explain health and disease determinants, from pure determinism in Koch postulates, accepting unicausal explanation for diseases, to more realistic multicausal models. In occupational health it is necessary to formulate causal models and criteria to assess causality, and frequently causal assessment in this field has important social, economic and juridical relevance. This paper deal with evaluation of causal relationships in epidemiology and this evaluation is illustrated with a recent example of an occupational health problem in our milieu: the Ardystil case. PMID:8666516

  7. Spin foam models as energetic causal sets

    NASA Astrophysics Data System (ADS)

    Cortês, Marina; Smolin, Lee

    2016-04-01

    Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations [M. Cortês and L. Smolin, Phys. Rev. D 90, 084007 (2014); Phys. Rev. D 90, 044035 (2014)]. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced in parallel by Wolfgang Wieland in [Classical Quantum Gravity 32, 015016 (2015)]. What makes a spin foam model also an energetic causal set is Wieland's identification of new degrees of freedom analogous to momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model. Our formulation also makes use of Markopoulou's causal formulation of spin foams [arXiv:gr-qc/9704013]. These are generated by evolving spin networks with dual Pachner moves. This endows the spin foam history with causal structure given by a partial ordering of the events which are dual to four-simplices.

  8. Learning a Theory of Causality

    ERIC Educational Resources Information Center

    Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B.

    2011-01-01

    The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…

  9. The causal relationship between education, health and health related behaviour: evidence from a natural experiment in England.

    PubMed

    Braakmann, Nils

    2011-07-01

    I exploit exogenous variation in the likelihood to obtain any sort of educational qualification between January- and February-born individuals for 13 academic cohorts in England. For these cohorts compulsory schooling laws interacted with the timing of the CSE and O-level exams to change the probability of obtaining a qualification by around 2-3 percentage points. I then use data on individuals born in these two months from the British Labour Force Survey and the Health Survey for England to investigate the effects of education on health using being February-born as an instrument for education. The results indicate neither an effect of education on various health related measures nor an effect on health related behaviour, e.g., smoking, drinking or eating various types of food. PMID:21715033

  10. Accelerated relative sea-level rise and rapid coastal erosion: Testing a causal relationship for the Louisiana barrier islands

    USGS Publications Warehouse

    List, J.H.; Sallenger, A.H., Jr.; Hansen, M.E.; Jaffe, B.E.

    1997-01-01

    The role of relative sea-level rise as a cause for the rapid erosion of Louisiana's barrier island coast is investigated through a numerical implementation of a modified Bruun rule that accounts for the low percentage of sand-sized sediment in the eroding Louisiana shoreface. Shore-normal profiles from 150 km of coastline west of the Mississippi delta are derived from bathymetric surveys conducted during the 1880s. 1930s and 1980s. An RMS difference criterion is employed to test whether an equilibrium profile form is maintained between survey years. Only about half the studied profiles meet the equilibrium Criterion this represents a significant limitation on the potential applicability of the Bruun rule. The profiles meeting the equilibrium criterion, along with measured rates of relative sea-level rise, are used to hindcast shoreline retreat rates at 37 locations within the study area. Modeled and observed shoreline retreat rates show no significant correlation. Thus in terms of the Bruun approach relative sea-level rise has no power for hindcasting (and presumably forecasting) rates of coastal erosion for the Louisiana barrier islands.

  11. Multisource causal data mining

    NASA Astrophysics Data System (ADS)

    Woodley, Robert; Gosnell, Michael; Shallenberger, Kevin

    2012-06-01

    Analysts are faced with mountains of data, and finding that relevant piece of information is the proverbial needle in a haystack, only with dozens of haystacks. Analysis tools that facilitate identifying causal relationships across multiple data sets are sorely needed. 21st Century Systems, Inc. (21CSi) has initiated research called Causal-View, a causal datamining visualization tool, to address this challenge. Causal-View is built on an agent-enabled framework. Much of the processing that Causal-View will do is in the background. When a user requests information, Data Extraction Agents launch to gather information. This initial search is a raw, Monte Carlo type search designed to gather everything available that may have relevance to an individual, location, associations, and more. This data is then processed by Data- Mining Agents. The Data-Mining Agents are driven by user supplied feature parameters. If the analyst is looking to see if the individual frequents a known haven for insurgents he may request information on his last known locations. Or, if the analyst is trying to see if there is a pattern in the individual's contacts, the mining agent can be instructed with the type and relevance of the information fields to look at. The same data is extracted from the database, but the Data Mining Agents customize the feature set to determine causal relationships the user is interested in. At this point, a Hypothesis Generation and Data Reasoning Agents take over to form conditional hypotheses about the data and pare the data, respectively. The newly formed information is then published to the agent communication backbone of Causal- View to be displayed. Causal-View provides causal analysis tools to fill the gaps in the causal chain. We present here the Causal-View concept, the initial research into data mining tools that assist in forming the causal relationships, and our initial findings.

  12. Granger causality revisited

    PubMed Central

    Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

    2014-01-01

    This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

  13. Causality & holographic entanglement entropy

    NASA Astrophysics Data System (ADS)

    Headrick, Matthew; Hubeny, Veronika E.; Lawrence, Albion; Rangamani, Mukund

    2014-12-01

    We identify conditions for the entanglement entropy as a function of spatial region to be compatible with causality in an arbitrary relativistic quantum field theory. We then prove that the covariant holographic entanglement entropy prescription (which relates entanglement entropy of a given spatial region on the boundary to the area of a certain extremal surface in the bulk) obeys these conditions, as long as the bulk obeys the null energy condition. While necessary for the validity of the prescription, this consistency requirement is quite nontrivial from the bulk standpoint, and therefore provides important additional evidence for the prescription. In the process, we introduce a codimension-zero bulk region, named the entanglement wedge, naturally associated with the given boundary spatial region. We propose that the entanglement wedge is the most natural bulk region corresponding to the boundary reduced density matrix.

  14. Granger causality and Atlantic hurricanes

    NASA Astrophysics Data System (ADS)

    Elsner, James B.

    2007-08-01

    Atlantic tropical cyclones have been getting stronger recently with a trend that is related to an increase in the late summer/early fall sea-surface temperature over the North Atlantic. Some studies attribute the increasing ocean warmth and hurricane intensity to a natural climate fluctuation, known as the Atlantic Multidecadal Oscillation; others suggest that climate change related to anthropogenic greenhouse gases emissions is the cause. Noting that the only difference between these two hypotheses is the causal connection between global mean near-surface air temperature (GT) and Atlantic sea-surface temperature (SST), the author previously showed how to use statistical tests to examine this hypothesis. Here the author expands on this research. In particular, a more comprehensive explanation of the techniques and additional tests and checks against misspecification are provided. The earlier results are confirmed in showing that preceding GT anomalies have a significant statistical relationship to current SST anomalies but not conversely so that if causality exists between Atlantic SST and global temperature, the causal direction likely goes from GT to SST. The result is robust against a small amount of noise added to the data. Identical tests applied to surrogate time series fail to identify causality as expected. The work underscores the importance of using data models to understand relationships between hurricanes and climate.

  15. Causal Learning Across Domains

    ERIC Educational Resources Information Center

    Schulz, Laura E.; Gopnik, Alison

    2004-01-01

    Five studies investigated (a) children's ability to use the dependent and independent probabilities of events to make causal inferences and (b) the interaction between such inferences and domain-specific knowledge. In Experiment 1, preschoolers used patterns of dependence and independence to make accurate causal inferences in the domains of…

  16. Causality in Classical Electrodynamics

    ERIC Educational Resources Information Center

    Savage, Craig

    2012-01-01

    Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…

  17. Repeated Causal Decision Making

    ERIC Educational Resources Information Center

    Hagmayer, York; Meder, Bjorn

    2013-01-01

    Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…

  18. Witnessing causal nonseparability

    NASA Astrophysics Data System (ADS)

    Araújo, Mateus; Branciard, Cyril; Costa, Fabio; Feix, Adrien; Giarmatzi, Christina; Brukner, Časlav

    2015-10-01

    Our common understanding of the physical world deeply relies on the notion that events are ordered with respect to some time parameter, with past events serving as causes for future ones. Nonetheless, it was recently found that it is possible to formulate quantum mechanics without any reference to a global time or causal structure. The resulting framework includes new kinds of quantum resources that allow performing tasks—in particular, the violation of causal inequalities—which are impossible for events ordered according to a global causal order. However, no physical implementation of such resources is known. Here we show that a recently demonstrated resource for quantum computation—the quantum switch—is a genuine example of ‘indefinite causal order’. We do this by introducing a new tool—the causal witness—which can detect the causal nonseparability of any quantum resource that is incompatible with a definite causal order. We show however that the quantum switch does not violate any causal inequality.

  19. Agency, time, and causality

    PubMed Central

    Widlok, Thomas

    2014-01-01

    Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition. PMID:25414683

  20. Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

    ERIC Educational Resources Information Center

    Johnson, Samuel G. B.; Ahn, Woo-kyoung

    2015-01-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different…

  1. Preschool Children Learn about Causal Structure from Conditional Interventions

    ERIC Educational Resources Information Center

    Schulz, Laura E.; Gopnik, Alison; Glymour, Clark

    2007-01-01

    The conditional intervention principle is a formal principle that relates patterns of interventions and outcomes to causal structure. It is a central assumption of experimental design and the causal Bayes net formalism. Two studies suggest that preschoolers can use the conditional intervention principle to distinguish causal chains, common cause…

  2. The Specification of Causal Models with Tetrad IV: A Review

    ERIC Educational Resources Information Center

    Landsheer, J. A.

    2010-01-01

    Tetrad IV is a program designed for the specification of causal models. It is specifically designed to search for causal relations, but also offers the possibility to estimate the parameters of a structural equation model. It offers a remarkable graphical user interface, which facilitates building, evaluating, and searching for causal models. The…

  3. How to Be Causal: Time, Spacetime and Spectra

    ERIC Educational Resources Information Center

    Kinsler, Paul

    2011-01-01

    I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers-Kronig relations. The specification of causality in terms of temporal differential equations then shows us the way to write down dynamical models so that their causal nature "in the sense used here" should be obvious to all. To extend existing…

  4. Causality and headache triggers

    PubMed Central

    Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.

    2013-01-01

    Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872

  5. Anterior cingulate cortex-related connectivity in first-episode schizophrenia: a spectral dynamic causal modeling study with functional magnetic resonance imaging

    PubMed Central

    Cui, Long-Biao; Liu, Jian; Wang, Liu-Xian; Li, Chen; Xi, Yi-Bin; Guo, Fan; Wang, Hua-Ning; Zhang, Lin-Chuan; Liu, Wen-Ming; He, Hong; Tian, Ping; Yin, Hong; Lu, Hongbing

    2015-01-01

    Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. PMID:26578933

  6. Causal Rasch models

    PubMed Central

    Stenner, A. Jackson; Fisher, William P.; Stone, Mark H.; Burdick, Donald S.

    2013-01-01

    Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained. PMID:23986726

  7. Analysing connectivity with Granger causality and dynamic causal modelling

    PubMed Central

    Friston, Karl; Moran, Rosalyn; Seth, Anil K

    2013-01-01

    This review considers state-of-the-art analyses of functional integration in neuronal macrocircuits. We focus on detecting and estimating directed connectivity in neuronal networks using Granger causality (GC) and dynamic causal modelling (DCM). These approaches are considered in the context of functional segregation and integration and — within functional integration — the distinction between functional and effective connectivity. We review recent developments that have enjoyed a rapid uptake in the discovery and quantification of functional brain architectures. GC and DCM have distinct and complementary ambitions that are usefully considered in relation to the detection of functional connectivity and the identification of models of effective connectivity. We highlight the basic ideas upon which they are grounded, provide a comparative evaluation and point to some outstanding issues. PMID:23265964

  8. The role of causal criteria in causal inferences: Bradford Hill's "aspects of association"

    PubMed Central

    Ward, Andrew C

    2009-01-01

    As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally – the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims. PMID:19534788

  9. Generalized Causal Mediation Analysis

    PubMed Central

    Albert, Jeffrey M.; Nelson, Suchitra

    2010-01-01

    Summary The goal of mediation analysis is to assess direct and indirect effects of a treatment or exposure on an outcome. More generally, we may be interested in the context of a causal model as characterized by a directed acyclic graph (DAG), where mediation via a specific path from exposure to outcome may involve an arbitrary number of links (or ‘stages’). Methods for estimating mediation (or pathway) effects are available for a continuous outcome and a continuous mediator related via a linear model, while for a categorical outcome or categorical mediator, methods are usually limited to two-stage mediation. We present a method applicable to multiple stages of mediation and mixed variable types using generalized linear models. We define pathway effects using a potential outcomes framework and present a general formula that provides the effect of exposure through any specified pathway. Some pathway effects are nonidentifiable and their estimation requires an assumption regarding the correlation between counterfactuals. We provide a sensitivity analysis to assess of the impact of this assumption. Confidence intervals for pathway effect estimates are obtained via a bootstrap method. The method is applied to a cohort study of dental caries in very low birth weight adolescents. A simulation study demonstrates low bias of pathway effect estimators and close-to-nominal coverage rates of confidence intervals. We also find low sensitivity to the counterfactual correlation in most scenarios. PMID:21306353

  10. Causal localizations in relativistic quantum mechanics

    SciTech Connect

    Castrigiano, Domenico P. L. Leiseifer, Andreas D.

    2015-07-15

    Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.

  11. Causal structures in Gauss-Bonnet gravity

    NASA Astrophysics Data System (ADS)

    Izumi, Keisuke

    2014-08-01

    We analyze causal structures in Gauss-Bonnet gravity. It is known that Gauss-Bonnet gravity potentially has superluminal propagation of gravitons due to its noncanonical kinetic terms. In a theory with superluminal modes, an analysis of causality based on null curves makes no sense, and thus, we need to analyze them in a different way. In this paper, using the method of the characteristics, we analyze the causal structure in Gauss-Bonnet gravity. We have the result that, on a Killing horizon, gravitons can propagate in the null direction tangent to the Killing horizon. Therefore, a Killing horizon can be a causal edge as in the case of general relativity; i.e. a Killing horizon is the "event horizon" in the sense of causality. We also analyze causal structures on nonstationary solutions with (D-2)-dimensional maximal symmetry, including spherically symmetric and flat spaces. If the geometrical null energy condition, RABNANB≥0 for any null vector NA, is satisfied, the radial velocity of gravitons must be less than or equal to that of light. However, if the geometrical null energy condition is violated, gravitons can propagate faster than light. Hence, on an evaporating black hole where the geometrical null energy condition is expected not to hold, classical gravitons can escape from the "black hole" defined with null curves. That is, the causal structures become nontrivial. It may be one of the possible solutions for the information loss paradox of evaporating black holes.

  12. The gravity dual of boundary causality

    NASA Astrophysics Data System (ADS)

    Engelhardt, Netta; Fischetti, Sebastian

    2016-09-01

    In gauge/gravity duality, points which are not causally related on the boundary cannot be causally related through the bulk; this is the statement of boundary causality. By the Gao–Wald theorem, the averaged null energy condition in the bulk is sufficient to ensure this property. Here we proceed in the converse direction: we derive a necessary as well as sufficient condition for the preservation of boundary causality under perturbative (quantum or stringy) corrections to the bulk. The condition that we find is a (background-dependent) constraint on the amount by which light cones can ‘open’ over all null bulk geodesics. We show that this constraint is weaker than the averaged null energy condition.

  13. Information causality from an entropic and a probabilistic perspective

    SciTech Connect

    Al-Safi, Sabri W.; Short, Anthony J.

    2011-10-15

    The information causality principle is a generalization of the no-signaling principle which implies some of the known restrictions on quantum correlations. But despite its clear physical motivation, information causality is formulated in terms of a rather specialized game and figure of merit. We explore different perspectives on information causality, discussing the probability of success as the figure of merit, a relation between information causality and the nonlocal ''inner-product game,'' and the derivation of a quadratic bound for these games. We then examine an entropic formulation of information causality with which one can obtain the same results, arguably in a simpler fashion.

  14. Causality discovery technology

    NASA Astrophysics Data System (ADS)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

    2012-11-01

    Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

  15. Causal conditionals and counterfactuals

    PubMed Central

    Frosch, Caren A.; Byrne, Ruth M.J.

    2012-01-01

    Causal counterfactuals e.g., ‘if the ignition key had been turned then the car would have started’ and causal conditionals e.g., ‘if the ignition key was turned then the car started’ are understood by thinking about multiple possibilities of different sorts, as shown in six experiments using converging evidence from three different types of measures. Experiments 1a and 1b showed that conditionals that comprise enabling causes, e.g., ‘if the ignition key was turned then the car started’ primed people to read quickly conjunctions referring to the possibility of the enabler occurring without the outcome, e.g., ‘the ignition key was turned and the car did not start’. Experiments 2a and 2b showed that people paraphrased causal conditionals by using causal or temporal connectives (because, when), whereas they paraphrased causal counterfactuals by using subjunctive constructions (had…would have). Experiments 3a and 3b showed that people made different inferences from counterfactuals presented with enabling conditions compared to none. The implications of the results for alternative theories of conditionals are discussed. PMID:22858874

  16. Heavier smoking may lead to a relative increase in waist circumference: evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium

    PubMed Central

    Morris, Richard W; Taylor, Amy E; Fluharty, Meg E; Bjørngaard, Johan H; Åsvold, Bjørn Olav; Elvestad Gabrielsen, Maiken; Campbell, Archie; Marioni, Riccardo; Kumari, Meena; Korhonen, Tellervo; Männistö, Satu; Marques-Vidal, Pedro; Kaakinen, Marika; Cavadino, Alana; Postmus, Iris; Husemoen, Lise Lotte N; Skaaby, Tea; Ahluwalia, Tarun Veer Singh; Treur, Jorien L; Willemsen, Gonneke; Dale, Caroline; Wannamethee, S Goya; Lahti, Jari; Palotie, Aarno; Räikkönen, Katri; McConnachie, Alex; Padmanabhan, Sandosh; Wong, Andrew; Dalgård, Christine; Paternoster, Lavinia; Ben-Shlomo, Yoav; Tyrrell, Jessica; Horwood, John; Fergusson, David M; Kennedy, Martin A; Nohr, Ellen A; Christiansen, Lene; Kyvik, Kirsten Ohm; Kuh, Diana; Watt, Graham; Eriksson, Johan G; Whincup, Peter H; Vink, Jacqueline M; Boomsma, Dorret I; Davey Smith, George; Lawlor, Debbie; Linneberg, Allan; Ford, Ian; Jukema, J Wouter; Power, Chris; Hyppönen, Elina; Jarvelin, Marjo-Riitta; Preisig, Martin; Borodulin, Katja; Kaprio, Jaakko; Kivimaki, Mika; Smith, Blair H; Hayward, Caroline; Romundstad, Pål R; Sørensen, Thorkild I A; Munafò, Marcus R; Sattar, Naveed

    2015-01-01

    Objectives To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity. Design Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes. Participants 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). Primary outcome measures Waist and hip circumferences, and waist-hip ratio. Results The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by −0.40% (95% CI −0.57% to −0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being −0.31% (95% CI −0.42% to −0.19), −0.08% (−0.19% to 0.03%) and −0.74% (−0.96% to −0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (−0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (−0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele. Conclusions For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity. PMID:26264275

  17. Transitive reasoning distorts induction in causal chains.

    PubMed

    von Sydow, Momme; Hagmayer, York; Meder, Björn

    2016-04-01

    A probabilistic causal chain A→B→C may intuitively appear to be transitive: If A probabilistically causes B, and B probabilistically causes C, A probabilistically causes C. However, probabilistic causal relations can only guaranteed to be transitive if the so-called Markov condition holds. In two experiments, we examined how people make probabilistic judgments about indirect relationships A→C in causal chains A→B→C that violate the Markov condition. We hypothesized that participants would make transitive inferences in accordance with the Markov condition although they were presented with counterevidence showing intransitive data. For instance, participants were successively presented with data entailing positive dependencies A→B and B→C. At the same time, the data entailed that A and C were statistically independent. The results of two experiments show that transitive reasoning via a mediating event B influenced and distorted the induction of the indirect relation between A and C. Participants' judgments were affected by an interaction of transitive, causal-model-based inferences and the observed data. Our findings support the idea that people tend to chain individual causal relations into mental causal chains that obey the Markov condition and thus allow for transitive reasoning, even if the observed data entail that such inferences are not warranted. PMID:26620811

  18. Sensing the Coherence of Biology in Contrast to Psychology: Young Children’s Use of Causal Relations to Distinguish Two Foundational Domains

    PubMed Central

    Erickson, Jane E.; Keil, Frank C.; Lockhart, Kristi L.

    2011-01-01

    To what extent do children understand that biological processes fall into 1 coherent domain unified by distinct causal principles? In Experiments 1 and 2 (N = 125) kindergartners are given triads of biological and psychological processes and asked to identify which 2 members of the triad belong together. Results show that 5-year-olds correctly cluster biological processes and separate them from psychological ones. Experiments 3 and 4 (N = 64) examine whether or not children make this distinction because they understand that biological and psychological processes operate according to fundamentally different causal mechanisms. The results suggest that 5-year-olds do possess this understanding, and furthermore, they have intuitions about the nature of these different mechanisms. PMID:20331675

  19. Rate-Agnostic (Causal) Structure Learning

    PubMed Central

    Plis, Sergey; Danks, David; Freeman, Cynthia; Calhoun, Vince

    2016-01-01

    Causal structure learning from time series data is a major scientific challenge. Extant algorithms assume that measurements occur sufficiently quickly; more precisely, they assume approximately equal system and measurement timescales. In many domains, however, measurements occur at a significantly slower rate than the underlying system changes, but the size of the timescale mismatch is often unknown. This paper develops three causal structure learning algorithms, each of which discovers all dynamic causal graphs that explain the observed measurement data, perhaps given undersampling. That is, these algorithms all learn causal structure in a “rate-agnostic” manner: they do not assume any particular relation between the measurement and system timescales. We apply these algorithms to data from simulations to gain insight into the challenge of undersampling. PMID:27182188

  20. Establishing causal coherence across sentences: an ERP study

    PubMed Central

    Kuperberg, Gina R.; Paczynski, Martin; Ditman, Tali

    2011-01-01

    This study examined neural activity associated with establishing causal relationships across sentences during online comprehension. ERPs were measured while participants read and judged the relatedness of three-sentence scenarios in which the final sentence was highly causally related, intermediately related and causally unrelated to its context. Lexico-semantic co-occurrence was matched across the three conditions using a Latent Semantic Analysis. Critical words in causally unrelated scenarios evoked a larger N400 than words in both highly causally related and intermediately related scenarios, regardless of whether they appeared before or at the sentence-final position. At midline sites, the N400 to intermediately related sentence-final words was attenuated to the same degree as to highly causally related words, but otherwise the N400 to intermediately related words fell in between that evoked by highly causally related and intermediately related words. No modulation of the Late Positivity/P600 component was observed across conditions. These results indicate that both simple and complex causal inferences can influence the earliest stages of semantically processing an incoming word. Further, they suggest that causal coherence, at the situation level, can influence incremental word-by-word discourse comprehension, even when semantic relationships between individual words are matched. PMID:20175676

  1. Models and Moves: Focusing on Dimensions of Causal Complexity To Achieve Deeper Scientific Understanding.

    ERIC Educational Resources Information Center

    Perkins, David N.; Grotzer, Tina A.

    This paper presents the results of a research project based on the Understandings of Consequence Project. This study motivated students to engage in inquiry in science classrooms. The complexity of the models is divided into four categories--underlying causality, relational causality, probabilistic causality, and emergent causality--and provides…

  2. Causality: Physics and Philosophy

    ERIC Educational Resources Information Center

    Chatterjee, Atanu

    2013-01-01

    Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…

  3. The Causal Asymmetry

    ERIC Educational Resources Information Center

    White, Peter A.

    2006-01-01

    It is hypothesized that there is a pervasive and fundamental bias in humans' understanding of physical causation: Once the roles of cause and effect are assigned to objects in interactions, people tend to overestimate the strength and importance of the causal object and underestimate that of the effect object in bringing about the outcome. This…

  4. Causal Premise Semantics

    ERIC Educational Resources Information Center

    Kaufmann, Stefan

    2013-01-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…

  5. Causal Responsibility and Counterfactuals

    ERIC Educational Resources Information Center

    Lagnado, David A.; Gerstenberg, Tobias; Zultan, Ro'i

    2013-01-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in…

  6. Evaluating Causal Models.

    ERIC Educational Resources Information Center

    Watt, James H., Jr.

    Pointing out that linear causal models can organize the interrelationships of a large number of variables, this paper contends that such models are particularly useful to mass communication research, which must by necessity deal with complex systems of variables. The paper first outlines briefly the philosophical requirements for establishing a…

  7. Illness causal beliefs in Turkish immigrants

    PubMed Central

    Minas, Harry; Klimidis, Steven; Tuncer, Can

    2007-01-01

    Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and

  8. Hymenoscyphus fraxineus vs. Hymenoscyphus albidus – A comparative light microscopic study on the causal agent of European ash dieback and related foliicolous, stroma-forming species

    PubMed Central

    Baral, Hans-Otto; Bemmann, Martin

    2014-01-01

    Five species of Hymenoscyphus that fruit on black stromatized parts of dead leaves of deciduous trees are presented, giving details on their morphological and ecological characteristics. Several of these species have previously been misplaced in rutstroemiaceous genera because of the presence of a substratal stroma. However, the heteropolar, scutuloid ascospores with an often hook-like lateral protrusion at the rounded apex and the ascus apical ring of the Hymenoscyphus-type represent two reliable morphological characteristics that, together with molecular data, provide clear evidence for their placement in the genus Hymenoscyphus (Helotiaceae). Among the species treated is Hymenoscyphus fraxineus (=Hymenoscyphus pseudoalbidus), the causal agent of the European ash dieback disease. Since 1992 this species started within Europe to replace the rather uncommon Hymenoscyphus albidus, which is likewise confined to leaves of Fraxinus. Hy. fraxineus has been recorded already since 1990 in Eastern Asia (Japan, Korea, northeast of China), where it had been initially misidentified as Lambertella albida (≡Hy. albidus). In these regions, it occurs as a harmless saprotroph on Fraxinus mandshurica and Fraxinus rhynchophylla, suggesting that those populations are native while the European ash dieback disease has a recent Eastern Asiatic origin. The distinctly higher genetic diversity found in Japanese Hy. fraxineus in contrast to European Hy. fraxineus supports this view. Genetic similarities between Japanese Hy. fraxineus and European Hy. albidus suggest that also Hy. albidus might be a descendant of Asian Hy. fraxineus, though having invaded Europe much earlier. However, consistent genetic deviation between European and Asian Hy. fraxineus at two nucleotide positions of the ITS region indicates that the European ash disease originates from a region different from the presently known areas in Eastern Asia. Our results underline the importance of detailed morphological studies

  9. Causal Status and Coherence in Causal-Based Categorization

    ERIC Educational Resources Information Center

    Rehder, Bob; Kim, ShinWoo

    2010-01-01

    Research has documented two effects of interfeature causal knowledge on classification. A "causal status effect" occurs when features that are causes are more important to category membership than their effects. A "coherence effect" occurs when combinations of features that are consistent with causal laws provide additional evidence of category…

  10. Optimal causal inference: Estimating stored information and approximating causal architecture

    NASA Astrophysics Data System (ADS)

    Still, Susanne; Crutchfield, James P.; Ellison, Christopher J.

    2010-09-01

    We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding—a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.

  11. Causal Discovery of Dynamic Systems

    ERIC Educational Resources Information Center

    Voortman, Mark

    2010-01-01

    Recently, several philosophical and computational approaches to causality have used an interventionist framework to clarify the concept of causality [Spirtes et al., 2000, Pearl, 2000, Woodward, 2005]. The characteristic feature of the interventionist approach is that causal models are potentially useful in predicting the effects of manipulations.…

  12. Causal Cohesion and Story Coherence.

    ERIC Educational Resources Information Center

    Trabasso, Tom; And Others

    Based on the theory that a story's coherence depends directly on the causal cohesiveness of the story's individual events, this paper describes (1) a process by which readers use causal reasoning to connect events, (2) what memory representations result from this reasoning, and (3) the implications of test data on causal reasoning. Following a…

  13. Do tachyons violate the causality principle?

    NASA Astrophysics Data System (ADS)

    Nibart, Gilles

    2000-05-01

    Very early, A. EINSTEIN has shown that particles with velocities greater than the velocity of light in vacuum may produce causal anomalies. Later, in quantum mechanics CPT transformations have allowed causal loops at a microscopic scale. So the possibility of faster-than-light particles has been analyzed again. The Meta-Relativity has extended the special theory of Relativity to particles beyond the light barrier (tachyons), by using the relativist formula with complex values. It has assigned to any tachyon an imaginary proper mass which does not easily offer a physical interpretation. In the framework of that theory, tachyons may appear to travel backwards in time and have negative energies, but they have to be interpreted as travelling forwards in time with positive energies (reinterpretation principle). The Meta-Relativity allows a tachyon reflection or re-emission to produce a causal loop, but some authors rejects the objection by postulating the tachyon emission cannot be systematically repeated. So causal loops can only occur at a microscopic scale. The theory of Relativity in the spacelike region has been developed by R. DUTHEIL using the tensor formalism of the general theory of Relativity. He defined tachyonic referential frames (TRF) with an other metric tensor and he showed it leads to an other LORENTZ group of transformations—the superluminal LORENTZ group. In this theory, tachyons always have a positive energy and a real proper mass, but their behavior must be described with tachyonic referential frames. R. DUTHEIL argued from the isomorphism of the both LORENTZ groups to prove the ZEEMAN'S theorem is respected by tachyons; so a sequence order is always preserved by any superluminal transformation. In the present communication, I show that time coordinates of tachyonic referential frames do not preserve causal order and do not make sense for natural observers. Nevertheless I show that the causal order is preserved within the superluminal proper time

  14. Causal Responsibility and Counterfactuals

    PubMed Central

    Lagnado, David A; Gerstenberg, Tobias; Zultan, Ro'i

    2013-01-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. PMID:23855451

  15. Are fetal growth impairment and preterm birth causally related to child attention problems and ADHD? Evidence from a comparison between high-income and middle-income cohorts

    PubMed Central

    Murray, Elizabeth; Pearson, Rebecca; Fernandes, Michelle; Santos, Iná S; Barros, Fernando C; Victora, Cesar G; Stein, Alan; Matijasevich, Alicia

    2016-01-01

    Background Cross-cohort comparison is an established method for improving causal inference. This study compared 2 cohorts, 1 from a high-income country and another from a middle-income country, to (1) establish whether birth exposures may play a causal role in the development of childhood attention problems; and (2) identify whether confounding structures play a different role in parent-reported attention difficulties compared with attention deficit hyperactivity disorder (ADHD) diagnoses. Methods Birth exposures included low birth weight (LBW), small-for-gestational age (SGA), small head circumference (HC) and preterm birth (PTB)). Outcomes of interest were attention difficulties (Strengths and Difficulties Questionnaire, SDQ) and ADHD (Development and Well-Being Assessment, DAWBA). Associations between exposures and outcomes were compared between 7-year-old children from the Avon Longitudinal Study of Parents and Children (ALSPAC) in the UK (N=6849) and the 2004 Pelotas cohort in Brazil (N=3509). Results For attention difficulties (SDQ), the pattern of association with birth exposures was similar between cohorts: following adjustment, attention difficulties were associated with SGA (OR=1.59, 95% CI 1.20 to 2.19) and small HC (OR=1.64, 95% CI 1.11 to 2.41) in ALSPAC and SGA (OR=1.35, 95% CI 1.04 to 1.75) in Pelotas. For ADHD, however, the pattern of association following adjustment differed markedly between cohorts. In ALSPAC, ADHD was associated with LBW (OR=2.29, 95% CI 1.09 to 4.80) and PTB (OR=2.33, 95% CI 1.23 to 4.42). In the Pelotas cohort, however, ADHD was associated with SGA (OR=1.69, 95% CI 1.02 to 2.82). Conclusions The findings suggest that fetal growth impairment may play a causal role in the development of attention difficulties in childhood, as similar associations were identified across both cohorts. Confounding structures, however, appear to play a greater role in determining whether a child meets the full diagnostic criteria for ADHD. PMID

  16. Non-Bayesian Inference: Causal Structure Trumps Correlation

    ERIC Educational Resources Information Center

    Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric

    2012-01-01

    The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…

  17. Quantum causality in closed timelike curves

    NASA Astrophysics Data System (ADS)

    Korotaev, S. M.; Kiktenko, E. O.

    2015-08-01

    Although general relativity allows the existence of closed timelike curves (CTCs), self-consistency problems arise (the ‘grandfather paradox’ among others). It is known that quantum mechanical consideration of the matter formally removes all the paradoxes, but the questions about causal structure remain. On the other hand, the idea of postselected CTCs (P-CTC) in quantum teleportation has know been put forward and experimentally implemented. We consider these problems with the aid of quantum causal analysis, where causality is defined without invoking the time relation. It implements the Cramer principle of weak causality, which admits time reversal in entangled states. We analyze Deutsch CTCs (D-CTC) with different kinds of interactions between the chronology-violating and chronology-respecting particles, with refined inferences about mixedness, quantum/classical correlations, entanglement and thermodynamics in the D-CTC. The main result is that time reversal causality can really exist, however, the final quantum state does not place retrospective constraints on the initial state, instead the final state can influence the state inside the D-CTC. This is effectively the implementation of Novikov self-consistency principle. The P-CTC has radically different properties; in particular, if the initial state was pure, the final state is always pure too. Self-consistency is controlled by the initial state-dependent traversability of the P-CTC.

  18. Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables

    NASA Astrophysics Data System (ADS)

    Barnett, Lionel; Barrett, Adam B.; Seth, Anil K.

    2009-12-01

    Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.

  19. Choice of Units and the Causal Markov Condition

    NASA Astrophysics Data System (ADS)

    Zhang, Jiji; Spirtes, Peter

    2014-03-01

    Elliott Sober's well-known challenge to the principle of the common cause -- and to its generalization, the causal Markov condition -- appeals to the apparent positive correlation between two causally unconnected quantities: Venetian sea levels and British bread prices. In this paper we examine Kevin Hoover's and Daniel Steel's opposite evaluations of Sober's case. We argue that the difference in their assessments results from a difference in their choice of units and populations for statistical modeling. Our analysis suggests yet another diagnosis of Sober's counterexample: the failure of the causal Markov condition in the population chosen by Sober and Steel is due to the presence of causal relations that hold between the relevant properties across units. Such inter-unit causation is left unrepresented in causal models congenial to statistical analysis, because statistics does not deal with inter-unit relationships once the units are fixed. Accordingly, the causal Markov condition is formulated in terms of causal structures that depict intra-unit causal relations only. It is therefore worth highlighting a methodological principle for causal inference: the units should be so chosen that they do not interfere with each other, a principle that, fortunately, is often observed in practice.

  20. Quantum information causality.

    PubMed

    Pitalúa-García, Damián

    2013-05-24

    How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs. PMID:23745844

  1. Causal Entropic Forces

    NASA Astrophysics Data System (ADS)

    Wissner-Gross, A. D.; Freer, C. E.

    2013-04-01

    Recent advances in fields ranging from cosmology to computer science have hinted at a possible deep connection between intelligence and entropy maximization, but no formal physical relationship between them has yet been established. Here, we explicitly propose a first step toward such a relationship in the form of a causal generalization of entropic forces that we find can cause two defining behaviors of the human “cognitive niche”—tool use and social cooperation—to spontaneously emerge in simple physical systems. Our results suggest a potentially general thermodynamic model of adaptive behavior as a nonequilibrium process in open systems.

  2. Aging and Retrospective Revaluation of Causal Learning

    PubMed Central

    Mutter, Sharon A.; Atchley, Anthony R.; Plumlee, Leslie M.

    2011-01-01

    In a two-stage causal learning task, young and older participants first learned which foods presented in compound were followed by an allergic reaction (e.g., STEAK - BEANS → REACTION) and then the causal efficacy of one food from these compounds was revalued (e.g., BEANS → NO REACTION). In Experiment 1, unrelated food pairs were used and although there were no age differences in compound or single cue – outcome learning, older adults did not retrospectively revalue the causal efficacy of the absent target cues (e.g. STEAK). However, they had weaker within – compound associations for the unrelated foods and this may have prevented them from retrieving the representations of these cues. In Experiment 2, older adults still showed no retrospective revaluation of absent cues even though compound food cues with pre-existing associations were used (e.g., STEAK - POTATO) and they received additional learning trials. Finally, in Experiment 3, older adults revalued the causal efficacy of the target cues when small, unobtrusive icons of these cues were present during single cue revaluation. These findings suggest that age – related deficits in causal learning for absent cues are due to ineffective associative binding and reactivation processes. PMID:21843025

  3. On causality in polymer scalar field theory

    NASA Astrophysics Data System (ADS)

    García-Chung, Angel A.; Morales-Técotl, Hugo A.

    2011-10-01

    The properties of spacetime corresponding to a proposed quantum gravity theory might modify the high energy behavior of quantum fields. Motivated by loop quantum gravity, recently, Hossain et al [1] have considered a polymer field algebra that replaces the standard canonical one in order to calculate the propagator of a real scalar field in flat spacetime. This propagator features Lorentz violations. Motivated by the relation between Lorentz invariance and causality in standard Quantum Field Theory, in this work we investigate the causality behavior of the polymer scalar field.

  4. Causal structure of general relativistic spacetimes

    SciTech Connect

    Howard, Ecaterina

    2010-06-15

    We present some of the recent results and open questions on the causality problem in General Relativity. The concept of singularity is intimately connected with future trapped surface and inner event horizon formation. We offer a brief overview of the Hawking-Penrose singularity theorems and discuss a few open problems concerning the future Cauchy development (domain of dependence), break-down criteria and energy conditions for the horizon stability. A key question is whether causality violating regions, generating a Cauchy horizon are allowed.We raise several questions concerning the invisibility and stability of closed trapped surfaces from future null infinity and derive the imprisonment conditions. We provide an up-to-date perspective of the causal boundaries and spacelike conformal boundary extensions for time oriented Lorentzian manifolds and more exotic settings.

  5. Causal Phenotype Discovery via Deep Networks

    PubMed Central

    Kale, David C.; Che, Zhengping; Bahadori, Mohammad Taha; Li, Wenzhe; Liu, Yan; Wetzel, Randall

    2015-01-01

    The rapid growth of digital health databases has attracted many researchers interested in using modern computational methods to discover and model patterns of health and illness in a research program known as computational phenotyping. Much of the work in this area has focused on traditional statistical learning paradigms, such as classification, prediction, clustering, pattern mining. In this paper, we propose a related but different paradigm called causal phenotype discovery, which aims to discover latent representations of illness that are causally predictive. We illustrate this idea with a two-stage framework that combines the latent representation learning power of deep neural networks with state-of-the-art tools from causal inference. We apply this framework to two large ICU time series data sets and show that it can learn features that are predictively useful, that capture complex physiologic patterns associated with critical illnesses, and that are potentially more clinically meaningful than manually designed features. PMID:26958203

  6. Component Abilities of Children's Causal Reasoning

    ERIC Educational Resources Information Center

    Berzonsky, Michael D.

    1975-01-01

    Presents a study to determine, via scalogram analysis, whether there was a constant order in which children mastered six skills: understanding chance events, detecting incongruous causal relations, completing "because" statements, displaying a skeptical attitude, and explaining remote and familiar objects. Data were analyzed for 84 first-graders.…

  7. Causality, Confirmation, Credulity, and Structural Equation Modeling.

    ERIC Educational Resources Information Center

    Biddle, Bruce J.; Marlin, Marjorie M.

    1987-01-01

    Defines structural equation modeling (SEM) and points out its relation to other more familiar data-analytic techniques, as well as some of the potentials and pitfalls of SEM in the analysis of developmental data. Discussion focuses on causal modeling, path diagrams, ordinary least-squares regression analysis, and powerful methods for model…

  8. A Causal Model of Faculty Turnover Intentions.

    ERIC Educational Resources Information Center

    Smart, John C.

    1990-01-01

    A causal model assesses the relative influence of individual attributes, institutional characteristics, contextual-work environment variables, and multiple measures of job satisfaction on faculty intentions to leave their current institutions. Factors considered include tenure status, age, institutional status, governance style, organizational…

  9. Experimental test of nonlocal causality.

    PubMed

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro

    2016-08-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045

  10. Redundant variables and Granger causality

    NASA Astrophysics Data System (ADS)

    Angelini, L.; de Tommaso, M.; Marinazzo, D.; Nitti, L.; Pellicoro, M.; Stramaglia, S.

    2010-03-01

    We discuss the use of multivariate Granger causality in presence of redundant variables: the application of the standard analysis, in this case, leads to under estimation of causalities. Using the un-normalized version of the causality index, we quantitatively develop the notions of redundancy and synergy in the frame of causality and propose two approaches to group redundant variables: (i) for a given target, the remaining variables are grouped so as to maximize the total causality and (ii) the whole set of variables is partitioned to maximize the sum of the causalities between subsets. We show the application to a real neurological experiment, aiming to a deeper understanding of the physiological basis of abnormal neuronal oscillations in the migraine brain. The outcome by our approach reveals the change in the informational pattern due to repetitive transcranial magnetic stimulations.

  11. Experimental test of nonlocal causality

    PubMed Central

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G.; Fedrizzi, Alessandro

    2016-01-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell’s local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045

  12. Manifest Variable Granger Causality Models for Developmental Research: A Taxonomy

    ERIC Educational Resources Information Center

    von Eye, Alexander; Wiedermann, Wolfgang

    2015-01-01

    Granger models are popular when it comes to testing hypotheses that relate series of measures causally to each other. In this article, we propose a taxonomy of Granger causality models. The taxonomy results from crossing the four variables Order of Lag, Type of (Contemporaneous) Effect, Direction of Effect, and Segment of Dependent Series…

  13. Thinking Fast and Slow about Causality: Response to Palinkas

    ERIC Educational Resources Information Center

    Marsh, Jeanne C.

    2014-01-01

    Larry Palinkas advances the developing science of social work by providing an explanation of how social science research methods, both qualitative and quantitative, can improve our capacity to draw casual inferences. Understanding causal relations and making causal inferences--with the promise of being able to predict and control outcomes--is…

  14. Causal Discourse Analyzer: Improving Automated Feedback on Academic ESL Writing

    ERIC Educational Resources Information Center

    Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel

    2016-01-01

    Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…

  15. The Role of Functional Form in Causal-Based Categorization

    ERIC Educational Resources Information Center

    Rehder, Bob

    2015-01-01

    Two experiments tested how the "functional form" of the causal relations that link features of categories affects category-based inferences. Whereas "independent causes" can each bring about an effect by themselves, "conjunctive causes" all need to be present for an effect to occur. The causal model view of category…

  16. Structural Equations and Causal Explanations: Some Challenges for Causal SEM

    ERIC Educational Resources Information Center

    Markus, Keith A.

    2010-01-01

    One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…

  17. The lesson of causal discovery algorithms for quantum correlations: causal explanations of Bell-inequality violations require fine-tuning

    NASA Astrophysics Data System (ADS)

    Wood, Christopher J.; Spekkens, Robert W.

    2015-03-01

    An active area of research in the fields of machine learning and statistics is the development of causal discovery algorithms, the purpose of which is to infer the causal relations that hold among a set of variables from the correlations that these exhibit . We apply some of these algorithms to the correlations that arise for entangled quantum systems. We show that they cannot distinguish correlations that satisfy Bell inequalities from correlations that violate Bell inequalities, and consequently that they cannot do justice to the challenges of explaining certain quantum correlations causally. Nonetheless, by adapting the conceptual tools of causal inference, we can show that any attempt to provide a causal explanation of nonsignalling correlations that violate a Bell inequality must contradict a core principle of these algorithms, namely, that an observed statistical independence between variables should not be explained by fine-tuning of the causal parameters. In particular, we demonstrate the need for such fine-tuning for most of the causal mechanisms that have been proposed to underlie Bell correlations, including superluminal causal influences, superdeterminism (that is, a denial of freedom of choice of settings), and retrocausal influences which do not introduce causal cycles.

  18. Causal electromagnetic interaction equations

    SciTech Connect

    Zinoviev, Yury M.

    2011-02-15

    For the electromagnetic interaction of two particles the relativistic causal quantum mechanics equations are proposed. These equations are solved for the case when the second particle moves freely. The initial wave functions are supposed to be smooth and rapidly decreasing at the infinity. This condition is important for the convergence of the integrals similar to the integrals of quantum electrodynamics. We also consider the singular initial wave functions in the particular case when the second particle mass is equal to zero. The discrete energy spectrum of the first particle wave function is defined by the initial wave function of the free-moving second particle. Choosing the initial wave functions of the free-moving second particle it is possible to obtain a practically arbitrary discrete energy spectrum.

  19. Causality and cosmic inflation

    SciTech Connect

    Vachaspati, Tanmay; Trodden, Mark

    2000-01-15

    In the context of inflationary models with a pre-inflationary stage, in which the Einstein equations are obeyed, the null energy condition is satisfied, and spacetime topology is trivial, we argue that homogeneity on super-Hubble scales must be assumed as an initial condition. Models in which inflation arises from field dynamics in a Friedmann-Robertson-Walker background fall into this class but models in which inflation originates at the Planck epoch may evade this conclusion. Our arguments rest on causality and general relativistic constraints on the structure of spacetime. We discuss modifications to existing scenarios that may avoid the need for initial large-scale homogeneity. (c) 1999 The American Physical Society.

  20. Bell's theorem and the causal arrow of time

    NASA Astrophysics Data System (ADS)

    Argaman, Nathan

    2010-10-01

    Einstein held that the formalism of quantum mechanics involves "spooky actions at a distance." In the 1960s, Bell amplified this by showing that the predictions of quantum mechanics disagree with the results of any locally causal description. It should be appreciated that accepting nonlocal descriptions while retaining causality leads to a clash with relativity. Furthermore, the causal arrow of time by definition contradicts time-reversal symmetry. For these reasons, Wheeler and Feynman, Costa de Beauregard, Cramer, Price, and others have advocated abandoning microscopic causality. In this paper, a simplistic but concrete example of this line of thought is presented, in the form of a retro-causal toy model that is stochastic and provides an appealing description of the quantum correlations discussed by Bell. It is concluded that Einstein's "spooky actions" may occur "in the past" rather than "at a distance," resolving the tension between quantum mechanics and relativity and opening unexplored possibilities for future reformulations of quantum mechanics.

  1. Theory-Based Causal Induction

    ERIC Educational Resources Information Center

    Griffiths, Thomas L.; Tenenbaum, Joshua B.

    2009-01-01

    Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…

  2. Causal Learning with Local Computations

    ERIC Educational Resources Information Center

    Fernbach, Philip M.; Sloman, Steven A.

    2009-01-01

    The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require…

  3. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  4. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  5. Paradoxical Behavior of Granger Causality

    NASA Astrophysics Data System (ADS)

    Witt, Annette; Battaglia, Demian; Gail, Alexander

    2013-03-01

    Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen

  6. CausalTrail: Testing hypothesis using causal Bayesian networks

    PubMed Central

    Trampert, Patrick; Lenhof, Hans-Peter

    2015-01-01

    Summary Causal Bayesian Networks are a special class of Bayesian networks in which the hierarchy directly encodes the causal relationships between the variables. This allows to compute the effect of interventions, which are external changes to the system, caused by e.g. gene knockouts or an administered drug. Whereas numerous packages for constructing causal Bayesian networks are available, hardly any program targeted at downstream analysis exists. In this paper we present CausalTrail, a tool for performing reasoning on causal Bayesian networks using the do-calculus. CausalTrail's features include multiple data import methods, a flexible query language for formulating hypotheses, as well as an intuitive graphical user interface. The program is able to account for missing data and thus can be readily applied in multi-omics settings where it is common that not all measurements are performed for all samples. Availability and Implementation CausalTrail is implemented in C++ using the Boost and Qt5 libraries. It can be obtained from https://github.com/dstoeckel/causaltrail PMID:26913195

  7. Causal beliefs about depression in different cultural groups—what do cognitive psychological theories of causal learning and reasoning predict?

    PubMed Central

    Hagmayer, York; Engelmann, Neele

    2014-01-01

    Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analyzed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given. PMID:25505432

  8. Causal beliefs about depression in different cultural groups-what do cognitive psychological theories of causal learning and reasoning predict?

    PubMed

    Hagmayer, York; Engelmann, Neele

    2014-01-01

    Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analyzed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given. PMID:25505432

  9. A Quantum Probability Model of Causal Reasoning

    PubMed Central

    Trueblood, Jennifer S.; Busemeyer, Jerome R.

    2012-01-01

    People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause) with diagnostic judgments (i.e., the conditional probability of a cause given an effect). The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment. PMID:22593747

  10. History, causality, and sexology.

    PubMed

    Money, John

    2003-08-01

    In 1896, Krafft-Ebing published Psychopathia Sexualis. Popularly defined as hereditary weakness or taintedness in the family pedigree, degeneracy was called upon as a causal explanation for perversions of the sexual instinct. Although Krafft-Ebing accepted Karl Ulrichs proposal that homosexuality could be innate and probably located in the brain, he paid little attention to neuropathological sexology. Alfred Binet challenged Krafft-Ebing's orthodoxy by explaining fetishism in terms of associative learning, to which Krafft-Ebing's response was that only those with a hereditary taint would be vulnerable. Thus did the venerable nature-nurture antithesis maintain its rhetoric, even to the present day. Krafft-Ebing died too soon to meet the Freudian challenge of endopsychic determinism, and too soon also to encounter the idea of a developmental multivariate outcome of what I have termed the lovemap. Like other brain maps, for example the languagemap, the lovemap requires an intact human brain in which to develop. The personalized content of the lovemap has access to the brain by way of the special senses. PMID:14533017

  11. ["Karoshi" and causal relationships].

    PubMed

    Hamajima, N

    1992-08-01

    This paper aims to introduce a measure for use by physicians for stating the degree of probable causal relationship for "Karoshi", ie, a sudden death from cerebrovascular diseases or ischemic heart diseases under occupational stresses, as well as to give a brief description for legal procedures associated with worker's compensation and civil trial in Japan. It is a well-used measure in epidemiology, "attributable risk percent (AR%)", which can be applied to describe the extent of contribution to "Karoshi" of the excess occupational burdens the deceased worker was forced to bear. Although several standards such as average occupational burdens for the worker, average occupational burdens for an ordinary worker, burdens in a nonoccupational life, and a complete rest, might be considered for the AR% estimation, the average occupational burdens for an ordinary worker should normally be utilized as a standard for worker's compensation. The adoption of AR% could be helpful for courts to make a consistent judgement whether "Karoshi" cases are compensatable or not. PMID:1392028

  12. Property Transmission: An Explanatory Account of the Role of Similarity Information in Causal Inference

    ERIC Educational Resources Information Center

    White, Peter A.

    2009-01-01

    Many kinds of common and easily observed causal relations exhibit property transmission, which is a tendency for the causal object to impose its own properties on the effect object. It is proposed that property transmission becomes a general and readily available hypothesis used to make interpretations and judgments about causal questions under…

  13. Space, time, and causality in the human brain.

    PubMed

    Woods, Adam J; Hamilton, Roy H; Kranjec, Alexander; Minhaus, Preet; Bikson, Marom; Yu, Jonathan; Chatterjee, Anjan

    2014-05-15

    The ability to perceive causality is a central human ability constructed from elemental spatial and temporal information present in the environment. Although the nature of causality has captivated philosophers and scientists since antiquity, the neural correlates of causality remain poorly understood. In the present study, we used functional magnetic resonance imaging (fMRI) to generate hypotheses for candidate brain regions related to component processes important for perceptual causality in the human brain: elemental space perception, elemental time perception, and decision-making (Experiment 1; n=16). We then used transcranial direct current stimulation (tDCS) to test neural hypotheses generated from the fMRI experiment (Experiment 2; n=16). In both experiments, participants judged causality in billiard-ball style launching events; a blue ball approaches and contacts a red ball. Spatial and temporal contributions to causal perception were assessed by parametrically varying the spatial linearity and the temporal delays of the movement of the balls. Experiment 1 demonstrated unique patterns of activation correlated with spatial, temporal, and decision-making components of causality perception. Using tDCS, we then tested hypotheses for the specific roles of the parietal and frontal cortices found in the fMRI experiment. Parietal stimulation only decreased participants' perception of causality based on spatial violations, while frontal stimulation made participants less likely to perceive causality based on violations of space and time. Converging results from fMRI and tDCS indicate that parietal cortices contribute to causal perception because of their specific role in processing spatial relations, while the frontal cortices contribute more generally, consistent with their role in decision-making. PMID:24561228

  14. Causal inference and developmental psychology.

    PubMed

    Foster, E Michael

    2010-11-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether the risk factor actually causes outcomes. Random assignment is not possible in many instances, and for that reason, psychologists must rely on observational studies. Such studies identify associations, and causal interpretation of such associations requires additional assumptions. Research in developmental psychology generally has relied on various forms of linear regression, but this methodology has limitations for causal inference. Fortunately, methodological developments in various fields are providing new tools for causal inference-tools that rely on more plausible assumptions. This article describes the limitations of regression for causal inference and describes how new tools might offer better causal inference. This discussion highlights the importance of properly identifying covariates to include (and exclude) from the analysis. This discussion considers the directed acyclic graph for use in accomplishing this task. With the proper covariates having been chosen, many of the available methods rely on the assumption of "ignorability." The article discusses the meaning of ignorability and considers alternatives to this assumption, such as instrumental variables estimation. Finally, the article considers the use of the tools discussed in the context of a specific research question, the effect of family structure on child development. PMID:20677855

  15. Principal stratification in causal inference.

    PubMed

    Frangakis, Constantine E; Rubin, Donald B

    2002-03-01

    Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority. PMID:11890317

  16. Causal-explanatory pluralism: How intentions, functions, and mechanisms influence causal ascriptions.

    PubMed

    Lombrozo, Tania

    2010-12-01

    Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual dependence or on physical connections. This paper argues that both approaches to causation are psychologically real, with different modes of explanation promoting judgments more or less consistent with each approach. Two sets of experiments isolate the contributions of counterfactual dependence and physical connections in causal ascriptions involving events with people, artifacts, or biological traits, and manipulate whether the events are construed teleologically or mechanistically. The findings suggest that when events are construed teleologically, causal ascriptions are sensitive to counterfactual dependence and relatively insensitive to the presence of physical connections, but when events are construed mechanistically, causal ascriptions are sensitive to both counterfactual dependence and physical connections. The conclusion introduces an account of causation, an "exportable dependence theory," that provides a way to understand the contributions of physical connections and teleology in terms of the functions of causal ascriptions. PMID:20801434

  17. Sentencing goals, causal attributions, ideology, and personality.

    PubMed

    Carroll, J S; Perkowitz, W T; Lurigio, A J; Weaver, F M

    1987-01-01

    Disparity in sentencing of criminals has been related to a variety of individual difference variables. We propose a framework establishing resonances or coherent patterns among sentencing goals, causal attributions, ideology, and personality. Two studies are described, one with law and criminology students, the other with probation officers. Relations among the different types of variables reveal two resonances among both students and officers. One comprises various conservative and moralistic elements: a tough, punitive stance toward crime; belief in individual causality for crime; high scores on authoritarianism, dogmatism, and internal locus of control; lower moral stage; and political conservatism. The second comprises various liberal elements: rehabilitation, belief in economic and other external determinants of crime, higher moral stage, and belief in the powers and responsibilities of government to correct social problems. Implications of these results are discussed for individual differences in sentencing, attribution theory, and attempts to reduce disparity. PMID:3820064

  18. The Significance of Causally Coupled, Stable Neuronal Assemblies for the Psychological Time Arrow

    NASA Astrophysics Data System (ADS)

    Atmanspacher, Harald; Filk, Thomas; Scheingraber, Herbert

    2005-10-01

    Stable neuronal assemblies are generally regarded as neural correlates of mental representations. Their temporal sequence corresponds to the experience of a direction of time, sometimes called the psychological time arrow. We show that the stability of particular, biophysically motivated models of neuronal assemblies, called coupled map lattices, is supported by causal interactions among neurons and obstructed by non-causal or anti-causal interactions among neurons. This surprising relation between causality and stability suggests that those neuronal assemblies that are stable due to causal neuronal interactions, and thus correlated with mental representations, generate a psychological time arrow. Yet this impact of causal interactions among neurons on the directed sequence of mental representations does not rule out the possibility of mentally less efficacious non-causal or anti-causal interactions among neurons.

  19. Schematic Patterns of Causal Evidence.

    ERIC Educational Resources Information Center

    Rholes, William S.; Walters, Jackie

    1982-01-01

    The study was to determine when the patterns of causal evidence proposed by Orvis, Cunningham and Kelly (1975) begin to function as schemata in the attributional process. One hundred forty-four subjects took part in the study. (RH)

  20. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness and Verbal Short-Term Memory in Reading Skills: A Review

    ERIC Educational Resources Information Center

    Melby-Lervag, Monica

    2012-01-01

    The acknowledgement that educational achievement is highly dependent on successful reading development, has led to extensive research on its underlying factors. Evidence clearly suggests that the relation between reading skills, phoneme awareness, rhyme awareness, and verbal short-term memory is more than a mere association. A strong argument has…

  1. Introduction to Causal Dynamical Triangulations

    NASA Astrophysics Data System (ADS)

    Görlich, Andrzej

    The method of causal dynamical triangulations is a non-perturbative and background-independent approach to quantum theory of gravity. In this review we present recent results obtained within the four dimensional model of causal dynamical triangulations. We describe the phase structure of the model and demonstrate how a macroscopic four-dimensional de Sitter universe emerges dynamically from the full gravitational path integral. We show how to reconstruct the effective action describing scale factor fluctuations from Monte Carlo data.

  2. Boundary terms for causal sets

    NASA Astrophysics Data System (ADS)

    Buck, Michel; Dowker, Fay; Jubb, Ian; Surya, Sumati

    2015-10-01

    We propose a family of boundary terms for the action of a causal set with a spacelike boundary. We show that in the continuum limit one recovers the Gibbons-Hawking-York boundary term in the mean. We also calculate the continuum limit of the mean causal set action for an Alexandrov interval in flat spacetime. We find that it is equal to the volume of the codimension-2 intersection of the two light-cone boundaries of the interval.

  3. A Complex Systems Approach to Causal Discovery in Psychiatry

    PubMed Central

    Saxe, Glenn N.; Statnikov, Alexander; Fenyo, David; Ren, Jiwen; Li, Zhiguo; Prasad, Meera; Wall, Dennis; Bergman, Nora; Briggs, Ernestine C.; Aliferis, Constantin

    2016-01-01

    Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach–the Complex Systems-Causal Network (CS-CN) method–designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a ‘gold standard’ dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry. PMID:27028297

  4. Deconstructing events: The neural bases for space, time, and causality

    PubMed Central

    Kranjec, Alexander; Cardillo, Eileen R.; Lehet, Matthew; Chatterjee, Anjan

    2013-01-01

    Space, time, and causality provide a natural structure for organizing our experience. These abstract categories allow us to think relationally in the most basic sense; understanding simple events require one to represent the spatial relations among objects, the relative durations of actions or movements, and links between causes and effects. The present fMRI study investigates the extent to which the brain distinguishes between these fundamental conceptual domains. Participants performed a one-back task with three conditions of interest (SPACE, TIME and CAUSALITY). Each condition required comparing relations between events in a simple verbal narrative. Depending on the condition, participants were instructed to either attend to the spatial, temporal, or causal characteristics of events, but between participants, each particular event relation appeared in all three conditions. Contrasts compared neural activity during each condition against the remaining two and revealed how thinking about events is deconstructed neurally. Space trials recruited neural areas traditionally associated with visuospatial processing, primarily bilateral frontal and occipitoparietal networks. Causality trials activated areas previously found to underlie causal thinking and thematic role assignment, such as left medial frontal, and left middle temporal gyri, respectively. Causality trials also produced activations in SMA, caudate, and cerebellum; cortical and subcortical regions associated with the perception of time at different timescales. The TIME contrast however, produced no significant effects. This pattern, indicating negative results for TIME trials, but positive effects for CAUSALITY trials in areas important for time perception, motivated additional overlap analyses to further probe relations between domains. The results of these analyses suggest a closer correspondence between time and causality than between time and space. PMID:21861674

  5. Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.

    PubMed

    Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt

    2016-01-01

    Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling. PMID:26470866

  6. Different Kinds of Causality in Event Cognition

    ERIC Educational Resources Information Center

    Radvansky, Gabriel A.; Tamplin, Andrea K.; Armendarez, Joseph; Thompson, Alexis N.

    2014-01-01

    Narrative memory is better for information that is more causally connected and occurs at event boundaries, such as a causal break. However, it is unclear whether there are common or distinct influences of causality. For the event boundaries that arise as a result of causal breaks, the events that follow may subsequently become more causally…

  7. Spatio-temporal Granger causality: a new framework

    PubMed Central

    Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

    2015-01-01

    That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

  8. Spatio-temporal Granger causality: a new framework.

    PubMed

    Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

    2013-10-01

    That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

  9. Confounding effects of indirect connections on causality estimation.

    PubMed

    Vakorin, Vasily A; Krakovska, Olga A; McIntosh, Anthony R

    2009-10-30

    Addressing the issue of effective connectivity, this study focuses on effects of indirect connections on inferring stable causal relations: partial transfer entropy. We introduce a Granger causality measure based on a multivariate version of transfer entropy. The statistic takes into account the influence of the rest of the network (environment) on observed coupling between two given nodes. This formalism allows us to quantify, for a specific pathway, the total amount of indirect coupling mediated by the environment. We show that partial transfer entropy is a more sensitive technique to identify robust causal relations than its bivariate equivalent. In addition, we demonstrate the confounding effects of the variation in indirect coupling on the detectability of robust causal links. Finally, we consider the problem of model misspecification and its effect on the robustness of the observed connectivity patterns, showing that misspecifying the model may be an issue even for model-free information-theoretic approach. PMID:19628006

  10. Causality in physiological signals.

    PubMed

    Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels

    2016-05-01

    Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The

  11. An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

    PubMed Central

    Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

    2016-01-01

    Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

  12. Causal reasoning with mental models

    PubMed Central

    Khemlani, Sangeet S.; Barbey, Aron K.; Johnson-Laird, Philip N.

    2014-01-01

    This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex. PMID:25389398

  13. Causal reasoning with mental models.

    PubMed

    Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N

    2014-01-01

    This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex. PMID:25389398

  14. Fluctuations in relativistic causal hydrodynamics

    NASA Astrophysics Data System (ADS)

    Kumar, Avdhesh; Bhatt, Jitesh R.; Mishra, Ananta P.

    2014-05-01

    Formalism to calculate the hydrodynamic fluctuations by applying the Onsager theory to the relativistic Navier-Stokes equation is already known. In this work, we calculate hydrodynamic fluctuations within the framework of the second order hydrodynamics of Müller, Israel and Stewart and its generalization to the third order. We have also calculated the fluctuations for several other causal hydrodynamical equations. We show that the form for the Onsager-coefficients and form of the correlation functions remain the same as those obtained by the relativistic Navier-Stokes equation and do not depend on any specific model of hydrodynamics. Further we numerically investigate evolution of the correlation function using the one dimensional boost-invariant (Bjorken) flow. We compare the correlation functions obtained using the causal hydrodynamics with the correlation function for the relativistic Navier-Stokes equation. We find that the qualitative behavior of the correlation functions remains the same for all the models of the causal hydrodynamics.

  15. Causal inference from observational data.

    PubMed

    Listl, Stefan; Jürges, Hendrik; Watt, Richard G

    2016-10-01

    Randomized controlled trials have long been considered the 'gold standard' for causal inference in clinical research. In the absence of randomized experiments, identification of reliable intervention points to improve oral health is often perceived as a challenge. But other fields of science, such as social science, have always been challenged by ethical constraints to conducting randomized controlled trials. Methods have been established to make causal inference using observational data, and these methods are becoming increasingly relevant in clinical medicine, health policy and public health research. This study provides an overview of state-of-the-art methods specifically designed for causal inference in observational data, including difference-in-differences (DiD) analyses, instrumental variables (IV), regression discontinuity designs (RDD) and fixed-effects panel data analysis. The described methods may be particularly useful in dental research, not least because of the increasing availability of routinely collected administrative data and electronic health records ('big data'). PMID:27111146

  16. Wormholes, baby universes, and causality

    SciTech Connect

    Visser, M. )

    1990-02-15

    In this paper wormholes defined on a Minkowski signature manifold are considered, both at the classical and quantum levels. It is argued that causality in quantum gravity may best be imposed by restricting the functional integral to include only causal Lorentzian spacetimes. Subject to this assumption, one can put very tight constraints on the quantum behavior of wormholes, their cousins the baby universes, and topology-changing processes in general. Even though topology-changing processes are tightly constrained, this still allows very interesting geometrical (rather than topological) effects. In particular, the laboratory construction of baby universes is {ital not} prohibited provided that the umbilical cord'' is never cut. Methods for relaxing these causality constraints are also discussed.

  17. "Head take you": causal attributions of mental illness in Jamaica.

    PubMed

    Arthur, Carlotta M; Whitley, Rob

    2015-02-01

    Causal attributions are a key factor in explanatory models of illness; however, little research on causal attributions of mental illness has been conducted in developing nations in the Caribbean, including Jamaica. Explanatory models of mental illness may be important in understanding illness experience and be a crucial factor in mental health service seeking and utilization. We explored causal attributions of mental illness in Jamaica by conducting 20 focus groups, including 16 community samples, 2 patient samples, and 2 samples of caregivers of patients, with a total of 159 participants. The 5 most commonly endorsed causal attributions of mental illness are discussed: (a) drug-related causes, including ganja (marijuana); (b) biological causes, such as chemical imbalance, familial transmission, and "blood"; (c) psychological causes, including stress and thinking too much; (d) social causes, such as relationship problems and job loss; and (e) spiritual or religious causes, including Obeah. PMID:25406259

  18. Methods for causal inference from gene perturbation experiments and validation.

    PubMed

    Meinshausen, Nicolai; Hauser, Alain; Mooij, Joris M; Peters, Jonas; Versteeg, Philip; Bühlmann, Peter

    2016-07-01

    Inferring causal effects from observational and interventional data is a highly desirable but ambitious goal. Many of the computational and statistical methods are plagued by fundamental identifiability issues, instability, and unreliable performance, especially for large-scale systems with many measured variables. We present software and provide some validation of a recently developed methodology based on an invariance principle, called invariant causal prediction (ICP). The ICP method quantifies confidence probabilities for inferring causal structures and thus leads to more reliable and confirmatory statements for causal relations and predictions of external intervention effects. We validate the ICP method and some other procedures using large-scale genome-wide gene perturbation experiments in Saccharomyces cerevisiae The results suggest that prediction and prioritization of future experimental interventions, such as gene deletions, can be improved by using our statistical inference techniques. PMID:27382150

  19. Methods for causal inference from gene perturbation experiments and validation

    PubMed Central

    Meinshausen, Nicolai; Hauser, Alain; Mooij, Joris M.; Peters, Jonas; Versteeg, Philip; Bühlmann, Peter

    2016-01-01

    Inferring causal effects from observational and interventional data is a highly desirable but ambitious goal. Many of the computational and statistical methods are plagued by fundamental identifiability issues, instability, and unreliable performance, especially for large-scale systems with many measured variables. We present software and provide some validation of a recently developed methodology based on an invariance principle, called invariant causal prediction (ICP). The ICP method quantifies confidence probabilities for inferring causal structures and thus leads to more reliable and confirmatory statements for causal relations and predictions of external intervention effects. We validate the ICP method and some other procedures using large-scale genome-wide gene perturbation experiments in Saccharomyces cerevisiae. The results suggest that prediction and prioritization of future experimental interventions, such as gene deletions, can be improved by using our statistical inference techniques. PMID:27382150

  20. Causal interpretation rules for encoding and decoding models in neuroimaging.

    PubMed

    Weichwald, Sebastian; Meyer, Timm; Özdenizci, Ozan; Schölkopf, Bernhard; Ball, Tonio; Grosse-Wentrup, Moritz

    2015-04-15

    Causal terminology is often introduced in the interpretation of encoding and decoding models trained on neuroimaging data. In this article, we investigate which causal statements are warranted and which ones are not supported by empirical evidence. We argue that the distinction between encoding and decoding models is not sufficient for this purpose: relevant features in encoding and decoding models carry a different meaning in stimulus- and in response-based experimental paradigms.We show that only encoding models in the stimulus-based setting support unambiguous causal interpretations. By combining encoding and decoding models trained on the same data, however, we obtain insights into causal relations beyond those that are implied by each individual model type. We illustrate the empirical relevance of our theoretical findings on EEG data recorded during a visuo-motor learning task. PMID:25623501

  1. Reasoning about Causal Relationships: Inferences on Causal Networks

    PubMed Central

    Rottman, Benjamin Margolin; Hastie, Reid

    2013-01-01

    Over the last decade, a normative framework for making causal inferences, Bayesian Probabilistic Causal Networks, has come to dominate psychological studies of inference based on causal relationships. The following causal networks—[X→Y→Z, X←Y→Z, X→Y←Z]—supply answers for questions like, “Suppose both X and Y occur, what is the probability Z occurs?” or “Suppose you intervene and make Y occur, what is the probability Z occurs?” In this review, we provide a tutorial for how normatively to calculate these inferences. Then, we systematically detail the results of behavioral studies comparing human qualitative and quantitative judgments to the normative calculations for many network structures and for several types of inferences on those networks. Overall, when the normative calculations imply that an inference should increase, judgments usually go up; when calculations imply a decrease, judgments usually go down. However, two systematic deviations appear. First, people’s inferences violate the Markov assumption. For example, when inferring Z from the structure X→Y→Z, people think that X is relevant even when Y completely mediates the relationship between X and Z. Second, even when people’s inferences are directionally consistent with the normative calculations, they are often not as sensitive to the parameters and the structure of the network as they should be. We conclude with a discussion of productive directions for future research. PMID:23544658

  2. Causal structure in categorical quantum mechanics

    NASA Astrophysics Data System (ADS)

    Lal, Raymond Ashwin

    Categorical quantum mechanics is a way of formalising the structural features of quantum theory using category theory. It uses compound systems as the primitive notion, which is formalised by using symmetric monoidal categories. This leads to an elegant formalism for describing quantum protocols such as quantum teleportation. In particular, categorical quantum mechanics provides a graphical calculus that exposes the information flow of such protocols in an intuitive way. However, the graphical calculus also reveals surprising features of these protocols; for example, in the quantum teleportation protocol, information appears to flow `backwards-in-time'. This leads to question of how causal structure can be described within categorical quantum mechanics, and how this might lead to insight regarding the structural compatibility between quantum theory and relativity. This thesis is concerned with the project of formalising causal structure in categorical quantum mechanics. We begin by studying an abstract view of Bell-type experiments, as described by `no-signalling boxes', and we show that under time-reversal no-signalling boxes generically become signalling. This conflicts with the underlying symmetry of relativistic causal structure. This leads us to consider the framework of categorical quantum mechanics from the perspective of relativistic causal structure. We derive the properties that a symmetric monoidal category must satisfy in order to describe systems in such a background causal structure. We use these properties to define a new type of category, and this provides a formal framework for describing protocols in spacetime. We explore this new structure, showing how it leads to an understanding of the counter-intuitive information flow of protocols in categorical quantum mechanics. We then find that the formal properties of our new structure are naturally related to axioms for reconstructing quantum theory, and we show how a reconstruction scheme based on

  3. An Efficient Two-Tier Causal Protocol for Mobile Distributed Systems

    PubMed Central

    Dominguez, Eduardo Lopez; Pomares Hernandez, Saul E.; Gomez, Gustavo Rodriguez; Medina, Maria Auxilio

    2013-01-01

    Causal ordering is a useful tool for mobile distributed systems (MDS) to reduce the non-determinism induced by three main aspects: host mobility, asynchronous execution, and unpredictable communication delays. Several causal protocols for MDS exist. Most of them, in order to reduce the overhead and the computational cost over wireless channels and mobile hosts (MH), ensure causal ordering at and according to the causal view of the Base Stations. Nevertheless, these protocols introduce certain disadvantage, such as unnecessary inhibition at the delivery of messages. In this paper, we present an efficient causal protocol for groupware that satisfies the MDS's constraints, avoiding unnecessary inhibitions and ensuring the causal delivery based on the view of the MHs. One interesting aspect of our protocol is that it dynamically adapts the causal information attached to each message based on the number of messages with immediate dependency relation, and this is not directly proportional to the number of MHs. PMID:23585828

  4. An efficient two-tier causal protocol for mobile distributed systems.

    PubMed

    Dominguez, Eduardo Lopez; Pomares Hernandez, Saul E; Gomez, Gustavo Rodriguez; Medina, Maria Auxilio

    2013-01-01

    Causal ordering is a useful tool for mobile distributed systems (MDS) to reduce the non-determinism induced by three main aspects: host mobility, asynchronous execution, and unpredictable communication delays. Several causal protocols for MDS exist. Most of them, in order to reduce the overhead and the computational cost over wireless channels and mobile hosts (MH), ensure causal ordering at and according to the causal view of the Base Stations. Nevertheless, these protocols introduce certain disadvantage, such as unnecessary inhibition at the delivery of messages. In this paper, we present an efficient causal protocol for groupware that satisfies the MDS's constraints, avoiding unnecessary inhibitions and ensuring the causal delivery based on the view of the MHs. One interesting aspect of our protocol is that it dynamically adapts the causal information attached to each message based on the number of messages with immediate dependency relation, and this is not directly proportional to the number of MHs. PMID:23585828

  5. On the concept of Bell’s local causality in local classical and quantum theory

    SciTech Connect

    Hofer-Szabó, Gábor; Vecsernyés, Péter

    2015-03-15

    The aim of this paper is to implement Bell’s notion of local causality into a framework, called local physical theory. This framework, based on the axioms of algebraic field theory, is broad enough to integrate both probabilistic and spatiotemporal concepts and also classical and quantum theories. Bell’s original idea of local causality will arise as the classical case of our definition. Classifying local physical theories by whether they obey local primitive causality, a property rendering the dynamics of the theory causal, we then investigate what is needed for a local physical theory to be locally causal. Finally, comparing local causality with the common cause principles and relating both to the Bell inequalities we find a nice parallelism: Bell inequalities cannot be derived neither from local causality nor from a common cause unless the local physical theory is classical or the common cause is commuting, respectively.

  6. Causal Models of Literacy Acquisition.

    ERIC Educational Resources Information Center

    Goetz, Ernest T.; And Others

    1992-01-01

    Examines seven articles that employed path analysis to test causal models of the acquisition of literacy or the reading-writing relationship. Reveals that, although such analysis holds promise for a better understanding of the components of literacy, several potential difficulties remain for those attempting to synthesize this body of literature.…

  7. Causality attribution biases oculomotor responses.

    PubMed

    Badler, Jeremy; Lefèvre, Philippe; Missal, Marcus

    2010-08-01

    When viewing one object move after being struck by another, humans perceive that the action of the first object "caused" the motion of the second, not that the two events occurred independently. Although established as a perceptual and linguistic concept, it is not yet known whether the notion of causality exists as a fundamental, preattentional "Gestalt" that can influence predictive motor processes. Therefore, eye movements of human observers were measured while viewing a display in which a launcher impacted a tool to trigger the motion of a second "reaction" target. The reaction target could move either in the direction predicted by transfer of momentum after the collision ("causal") or in a different direction ("noncausal"), with equal probability. Control trials were also performed with identical target motion, either with a 100 ms time delay between the collision and reactive motion, or without the interposed tool. Subjects made significantly more predictive movements (smooth pursuit and saccades) in the causal direction during standard trials, and smooth pursuit latencies were also shorter overall. These trends were reduced or absent in control trials. In addition, pursuit latencies in the noncausal direction were longer during standard trials than during control trials. The results show that causal context has a strong influence on predictive movements. PMID:20685994

  8. Causal Inference for a Population of Causally Connected Units

    PubMed Central

    van der Laan, Mark J.

    2015-01-01

    Suppose that we observe a population of causally connected units. On each unit at each time-point on a grid we observe a set of other units the unit is potentially connected with, and a unit-specific longitudinal data structure consisting of baseline and time-dependent covariates, a time-dependent treatment, and a final outcome of interest. The target quantity of interest is defined as the mean outcome for this group of units if the exposures of the units would be probabilistically assigned according to a known specified mechanism, where the latter is called a stochastic intervention. Causal effects of interest are defined as contrasts of the mean of the unit-specific outcomes under different stochastic interventions one wishes to evaluate. This covers a large range of estimation problems from independent units, independent clusters of units, and a single cluster of units in which each unit has a limited number of connections to other units. The allowed dependence includes treatment allocation in response to data on multiple units and so called causal interference as special cases. We present a few motivating classes of examples, propose a structural causal model, define the desired causal quantities, address the identification of these quantities from the observed data, and define maximum likelihood based estimators based on cross-validation. In particular, we present maximum likelihood based super-learning for this network data. Nonetheless, such smoothed/regularized maximum likelihood estimators are not targeted and will thereby be overly bias w.r.t. the target parameter, and, as a consequence, generally not result in asymptotically normally distributed estimators of the statistical target parameter. To formally develop estimation theory, we focus on the simpler case in which the longitudinal data structure is a point-treatment data structure. We formulate a novel targeted maximum likelihood estimator of this estimand and show that the double robustness of the

  9. Effects of question formats on causal judgments and model evaluation

    PubMed Central

    Smithson, Michael

    2015-01-01

    Evaluation of causal reasoning models depends on how well the subjects’ causal beliefs are assessed. Elicitation of causal beliefs is determined by the experimental questions put to subjects. We examined the impact of question formats commonly used in causal reasoning research on participant’s responses. The results of our experiment (Study 1) demonstrate that both the mean and homogeneity of the responses can be substantially influenced by the type of question (structure induction versus strength estimation versus prediction). Study 2A demonstrates that subjects’ responses to a question requiring them to predict the effect of a candidate cause can be significantly lower and more heterogeneous than their responses to a question asking them to diagnose a cause when given an effect. Study 2B suggests that diagnostic reasoning can strongly benefit from cues relating to temporal precedence of the cause in the question. Finally, we evaluated 16 variations of recent computational models and found the model fitting was substantially influenced by the type of questions. Our results show that future research in causal reasoning should place a high priority on disentangling the effects of question formats from the effects of experimental manipulations, because that will enable comparisons between models of causal reasoning uncontaminated by method artifact. PMID:25954225

  10. Causality and complexity: the myth of objectivity in science.

    PubMed

    Mikulecky, Donald C

    2007-10-01

    Two distinctly different worldviews dominate today's thinking in science and in the world of ideas outside of science. Using the approach advocated by Robert M. Hutchins, it is possible to see a pattern of interaction between ideas in science and in other spheres such as philosophy, religion, and politics. Instead of compartmentalizing these intellectual activities, it is worthwhile to look for common threads of mutual influence. Robert Rosen has created an approach to scientific epistemology that might seem radical to some. However, it has characteristics that resemble ideas in other fields, in particular in the writings of George Lakoff, Leo Strauss, and George Soros. Historically, the atmosphere at the University of Chicago during Hutchins' presidency gave rise to Rashevsky's relational biology, which Rosen carried forward. Strauss was writing his political philosophy there at the same time. One idea is paramount in all this, and it is Lakoff who gives us the most insight into how the worldviews differ using this idea. The central difference has to do with causality, the fundamental concept that we use to build a worldview. Causal entailment has two distinct forms in Lakoff 's analysis: direct causality and complex causality. Rosen's writings on complexity create a picture of complex causality that is extremely useful in its detail, grounding in the ideas of Aristotle. Strauss asks for a return to the ancients to put philosophy back on track. Lakoff sees the weaknesses in Western philosophy in a similar way, and Rosen provides tools for dealing with the problem. This introduction to the relationships between the thinking of these authors is meant to stimulate further discourse on the role of complex causal entailment in all areas of thought, and how it brings them together in a holistic worldview. The worldview built on complex causality is clearly distinct from that built around simple, direct causality. One important difference is that the impoverished causal

  11. Who Is the Dynamic Duo? How Infants Learn about the Identity of Objects in a Causal Chain

    ERIC Educational Resources Information Center

    Rakison, David H.; Smith, Gabriel Tobin; Ali, Areej

    2016-01-01

    Four experiments investigated infants' and adults' knowledge of the identity of objects in a causal sequence of events. In Experiments 1 and 2, 18- and 22-month-olds in the visual habituation procedure were shown a 3-step causal chain event in which the relation between an object's part (dynamic or static) and its causal role was either consistent…

  12. Children's and Adults' Memory for Television Stories: The Role of Causal Factors, Story-Grammar Categories, and Hierarchical Level.

    ERIC Educational Resources Information Center

    van den Broek, Paul; And Others

    1996-01-01

    Asked children and adults to recall events from "Sesame Street." Found that subjects' memory was influenced by causal factors (number of causal relations to other events, place in the story's causal chain) and this influence increased with age; children recalled actions, whereas adults recalled protagonists' goals; and children's recall increased…

  13. Expectations and Interpretations During Causal Learning

    PubMed Central

    Luhmann, Christian C.; Ahn, Woo-kyoung

    2012-01-01

    In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to expectations developed during causal learning, learners give varied interpretations to covariation information as it is encountered and that these interpretations influence the resulting causal beliefs. In Experiments 1A–1C, participants’ interpretations of observations during a causal learning task were dynamic, expectation based, and, furthermore, strongly tied to subsequent causal judgments. Experiment 2 demonstrated that adding trials of joint absence or joint presence of events, whose roles have been traditionally interpreted as increasing causal strengths, could result in decreased overall causal judgments and that adding trials where one event occurs in the absence of another, whose roles have been traditionally interpreted as decreasing causal strengths, could result in increased overall causal judgments. We discuss implications for traditional models of causal learning and how a more top-down approach (e.g., Bayesian) would be more compatible with the current findings. PMID:21534705

  14. Constraints on Children's Judgments of Magical Causality

    ERIC Educational Resources Information Center

    Woolley, Jacqueline D.; Browne, Cheryl A.; Boerger, Elizabeth A.

    2006-01-01

    In 3 studies we addressed the operation of constraints on children's causal judgments. Our primary focus was whether children's beliefs about magical causality, specifically wishing, are constrained by features that govern the attribution of ordinary causality. In Experiment 1, children witnessed situations in which a confederate's wish appeared…

  15. Designing Effective Supports for Causal Reasoning

    ERIC Educational Resources Information Center

    Jonassen, David H.; Ionas, Ioan Gelu

    2008-01-01

    Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and inferences, and…

  16. Representing Personal Determinants in Causal Structures.

    ERIC Educational Resources Information Center

    Bandura, Albert

    1984-01-01

    Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…

  17. Expectations and Interpretations during Causal Learning

    ERIC Educational Resources Information Center

    Luhmann, Christian C.; Ahn, Woo-kyoung

    2011-01-01

    In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…

  18. Does Causal Action Facilitate Causal Perception in Infants Younger than 6 Months of Age?

    ERIC Educational Resources Information Center

    Rakison, David H.; Krogh, Lauren

    2012-01-01

    Previous research has established that infants are unable to perceive causality until 6 1/4 months of age. The current experiments examined whether infants' ability to engage in causal action could facilitate causal perception prior to this age. In Experiment 1, 4 1/2-month-olds were randomly assigned to engage in causal action experience via…

  19. Modeling of causality with metamaterials

    NASA Astrophysics Data System (ADS)

    Smolyaninov, Igor I.

    2013-02-01

    Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space-time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space-time. While this model may be used to build interesting space-time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space-time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler-Feynman absorber theory of causality.

  20. Processing Causality in Narrative Events: Temporal Order Matters

    ERIC Educational Resources Information Center

    Briner, Stephen W.; Virtue, Sandra; Kurby, Christopher A.

    2012-01-01

    To successfully comprehend narrative text, readers often make inferences about different causes and effects that occur in a text. In this study, participants read texts in which events related to a cause were presented before an effect (i.e., the forward causal condition), texts in which an effect was presented before the events related to a cause…

  1. Causal Attributions and Recovery from Rape: Implications for Counseling.

    ERIC Educational Resources Information Center

    Frazier, Patricia A.; Schauben, Laura J.

    One factor related to postrape trauma is the survivor's belief about the cause of the rape. Most research to date on the relation between causal attributions and postrape recovery has been guided by a theoretical model which proposes that certain types of self-blame can be adaptive for survivors. Specifically, behavioral self-blame is thought to…

  2. Causal Asymmetry Across Cultures: Assigning Causal Roles in Symmetric Physical Settings

    PubMed Central

    Bender, Andrea; Beller, Sieghard

    2011-01-01

    Causal cognition in the physical domain has been treated for a long time as if it were (1) objective and (2) independent of culture. Despite some evidence to the contrary, however, these implicit assumptions have been rarely ever explored systematically. While the pervasive tendency of people to consider one of two equally important entities as more important for bringing about an effect (as reported by White, 2006) meanwhile provides one type of counter-evidence for the first assumption, respective findings remained mute to the second. In order to scrutinize how robust such tendencies are across cultures – and, if not, on which aspects of culture they may depend – we asked German and Tongan participants to assign prime causality in nine symmetric settings. For most settings, strong asymmetries in both cultures were found, but not always in the same direction, depending on the task content and by virtue of the multifaceted character of “culture.” This indicates that causal asymmetries, while indeed being a robust phenomenon across cultures, are also modulated by task-specific properties (such as figure–ground relations), and are subject to cultural influences. PMID:21960982

  3. Children's use of interventions to learn causal structure.

    PubMed

    McCormack, Teresa; Bramley, Neil; Frosch, Caren; Patrick, Fiona; Lagnado, David

    2016-01-01

    Children between 5 and 8 years of age freely intervened on a three-variable causal system, with their task being to discover whether it was a common cause structure or one of two causal chains. From 6 or 7 years of age, children were able to use information from their interventions to correctly disambiguate the structure of a causal chain. We used a Bayesian model to examine children's interventions on the system; this showed that with development children became more efficient in producing the interventions needed to disambiguate the causal structure and that the quality of interventions, as measured by their informativeness, improved developmentally. The latter measure was a significant predictor of children's correct inferences about the causal structure. A second experiment showed that levels of performance were not reduced in a task where children did not select and carry out interventions themselves, indicating no advantage for self-directed learning. However, children's performance was not related to intervention quality in these circumstances, suggesting that children learn in a different way when they carry out interventions themselves. PMID:26298433

  4. There aren't plenty more fish in the sea: a causal network approach.

    PubMed

    Nikolic, Milena; Lagnado, David A

    2015-11-01

    The current research investigated how lay representations of the causes of an environmental problem may underlie individuals' reasoning about the issue. Naïve participants completed an experiment that involved two main tasks. The causal diagram task required participants to depict the causal relations between a set of factors related to overfishing and to estimate the strength of these relations. The counterfactual task required participants to judge the effect of counterfactual suppositions based on the diagrammed factors. We explored two major questions: (1) what is the relation between individual causal models and counterfactual judgments? Consistent with previous findings (e.g., Green et al., 1998, Br. J. Soc. Psychology, 37, 415), these judgments were best explained by a combination of the strength of both direct and indirect causal paths. (2) To what extent do people use two-way causal thinking when reasoning about an environmental problem? In contrast to previous research (e.g., White, 2008, Appl. Cogn. Psychology, 22, 559), analyses based on individual causal networks revealed the presence of numerous feedback loops. The studies support the value of analysing individual causal models in contrast to consensual representations. Theoretical and practical implications are discussed in relation to causal reasoning as well as environmental psychology. PMID:25597224

  5. The latent causal chain of industrial water pollution in China.

    PubMed

    Miao, Xin; Tang, Yanhong; Wong, Christina W Y; Zang, Hongyu

    2015-01-01

    The purpose of this paper is to discover the latent causal chain of industrial water pollution in China and find ways to cure the want on discharge of toxic waste from industries. It draws evidences from the past pollution incidents in China. Through further digging the back interests and relations by analyzing representative cases, extended theory about loophole derivations and causal chain effect is drawn. This theoretical breakthrough reflects deeper causality. Institutional defect instead of human error is confirmed as the deeper reason of frequent outbreaks of water pollution incidents in China. Ways for collaborative environmental governance are proposed. This paper contributes to a better understanding about the deep inducements of industrial water pollution in China, and, is meaningful for ensuring future prevention and mitigation of environmental pollution. It illuminates multiple dimensions for collaborative environmental governance to cure the stubborn problem. PMID:25467695

  6. Causal diagrams in systems epidemiology

    PubMed Central

    2012-01-01

    Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed. The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties. The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets. Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback. PMID:22429606

  7. Comparison theorems for causal diamonds

    NASA Astrophysics Data System (ADS)

    Berthiere, Clément; Gibbons, Gary; Solodukhin, Sergey N.

    2015-09-01

    We formulate certain inequalities for the geometric quantities characterizing causal diamonds in curved and Minkowski spacetimes. These inequalities involve the redshift factor which, as we show explicitly in the spherically symmetric case, is monotonic in the radial direction, and it takes its maximal value at the center. As a by-product of our discussion we rederive Bishop's inequality without assuming the positivity of the spatial Ricci tensor. We then generalize our considerations to arbitrary, static and not necessarily spherically symmetric, asymptotically flat spacetimes. In the case of spacetimes with a horizon our generalization involves the so-called domain of dependence. The respective volume, expressed in terms of the duration measured by a distant observer compared with the volume of the domain in Minkowski spacetime, exhibits behaviors which differ if d =4 or d >4 . This peculiarity of four dimensions is due to the logarithmic subleading term in the asymptotic expansion of the metric near infinity. In terms of the invariant duration measured by a comoving observer associated with the diamond we establish an inequality which is universal for all d . We suggest some possible applications of our results including comparison theorems for entanglement entropy, causal set theory, and fundamental limits on computation.

  8. Orientation and Credibility: Implications for a Causal Relationship.

    ERIC Educational Resources Information Center

    Knutson, Thomas J.

    Orientation, in terms of the group discussion process, is the attempt to assist in achieving the group goals by using facts, making helpful suggestions, or resolving conflicts. Orientation behavior has been shown to relate in a causal manner to group consensus. This study reports significantly high positive correlations between orientation…

  9. The TETRAD Project: Constraint Based Aids to Causal Model Specification.

    ERIC Educational Resources Information Center

    Scheines, Richard; Spirtes, Peter; Glymour, Clark; Meek, Christopher; Richardson, Thomas

    1998-01-01

    The TETRAD for constraint-based aids to causal model specification project and related work in computer science aims to apply standards of rigor and precision to the problem of using data and background knowledge to make inferences about a model's specifications. Several algorithms that are implemented in the TETRAD II program are presented. (SLD)

  10. Music and Spatial Task Performance: A Causal Relationship.

    ERIC Educational Resources Information Center

    Rauscher, Frances H.; And Others

    This research paper reports on testing the hypothesis that music and spatial task performance are causally related. Two complementary studies are presented that replicate and explore previous findings. One study of college students showed that listening to a Mozart sonata induces subsequent short-term spatial reasoning facilitation and tested the…

  11. Timing and Causality in the Generation of Learned Eyelid Responses

    PubMed Central

    Sánchez-Campusano, Raudel; Gruart, Agnès; Delgado-García, José M.

    2011-01-01

    The cerebellum-red nucleus-facial motoneuron (Mn) pathway has been reported as being involved in the proper timing of classically conditioned eyelid responses. This special type of associative learning serves as a model of event timing for studying the role of the cerebellum in dynamic motor control. Here, we have re-analyzed the firing activities of cerebellar posterior interpositus (IP) neurons and orbicularis oculi (OO) Mns in alert behaving cats during classical eyeblink conditioning, using a delay paradigm. The aim was to revisit the hypothesis that the IP neurons (IPns) can be considered a neuronal phase-modulating device supporting OO Mns firing with an emergent timing mechanism and an explicit correlation code during learned eyelid movements. Optimized experimental and computational tools allowed us to determine the different causal relationships (temporal order and correlation code) during and between trials. These intra- and inter-trial timing strategies expanding from sub-second range (millisecond timing) to longer-lasting ranges (interval timing) expanded the functional domain of cerebellar timing beyond motor control. Interestingly, the results supported the above-mentioned hypothesis. The causal inferences were influenced by the precise motor and pre-motor spike timing in the cause-effect interval, and, in addition, the timing of the learned responses depended on cerebellar–Mn network causality. Furthermore, the timing of CRs depended upon the probability of simulated causal conditions in the cause-effect interval and not the mere duration of the inter-stimulus interval. In this work, the close relation between timing and causality was verified. It could thus be concluded that the firing activities of IPns may be related more to the proper performance of ongoing CRs (i.e., the proper timing as a consequence of the pertinent causality) than to their generation and/or initiation. PMID:21941469

  12. The concept of causality in image reconstruction

    SciTech Connect

    Llacer, J.; Veklerov, E.; Nunez, J.

    1988-09-01

    Causal images in emission tomography are defined as those which could have generated the data by the statistical process that governs the physics of the measurement. The concept of causality was previously applied to deciding when to stop the MLE iterative procedure in PET. The present paper further explores the concept, indicates the difficulty of carrying out a correct hypothesis testing for causality, discusses the assumption needed to justify the tests proposed and discusses a possible methodology for a justification of that assumption. The paper also describes several methods that we have found to generate causal images and it shows that the set of causal images is rather large. This set includes images judged to be superior to the best maximum likelihood images, but it also includes unacceptable and noisy images. The paper concludes by proposing to use causality as a constraint in optimization problems. 16 refs., 5 figs.

  13. A Cognition-Emotion-Action Sequence: Anticipated Emotional Consequences of Causal Attributions and Reported Communication Strategy.

    ERIC Educational Resources Information Center

    Weiner, Bernard; Handel, Stephen J.

    1985-01-01

    Examined development of relations between causal explanations, the anticipated emotional consequences for others if these causes were communicated, and the decision to disclose or withhold causal explanation. Within a role-playing paradigm, children aged 5-12 were given scenarios involving social rejection or broken social engagement. Data…

  14. Introducing Causality and Power into Family Therapy Theory: A Correction to the Systemic Paradigm.

    ERIC Educational Resources Information Center

    Fish, Vincent

    1990-01-01

    Proposes that concepts of causality and power are compatible with systemic paradigm based on cybernetics of Ashby rather than that of Bateson. Criticizes Bateson's repudiation of causality and power; addresses related Batesonian biases against "quantity" and "logic." Contrasts relevant aspects of Ashby's cybernetic theory with Batesonian…

  15. The Relationship between Battered Women's Causal Attributions for Violence and Coping Efforts

    ERIC Educational Resources Information Center

    Meyer, Alicia; Wagner, Barry; Dutton, Mary Ann

    2010-01-01

    This study investigates the relationship between battered women's causal attributions for the violence they experience and their subsequent coping efforts. Causal attributions related to partner blame, excusing the violence, and the combination of partner blame and excusing the violence were regressed on six categories of coping strategies:…

  16. Causal Attributions for Turnover by Supervisory and Non-supervisory Personnel.

    ERIC Educational Resources Information Center

    Krausz, Moshe; And Others

    1989-01-01

    Examined causal attributions for turnover of employees by supervisory (N=107) and non-supervisory (N=155) employees. Subjects rated extent of their agreement with two reasons for employee turnover: job dissatisfaction and external causes/family matters. Causal attributions of both groups were related to job attitudes: less satisfied subjects…

  17. Basic Language Skills and Young Children's Understanding of Causal Connections during Storytelling

    ERIC Educational Resources Information Center

    Brown, Danielle D.; Lile, Jacquelyn; Burns, Barbara M.

    2011-01-01

    The current study examined the role of basic language skills for individual differences in preschoolers' understanding of causal connections. Assessments of basic language skills, expressive vocabulary, phonological processing, and receptive language comprehension were examined in relation to the production of causal connections in a storytelling…

  18. Determining Subjectivity in Text: The Case of Backward Causal Connectives in Dutch

    ERIC Educational Resources Information Center

    Pit, Mirna

    2006-01-01

    This article addresses the question of how to systematically determine the degree of subjectivity expressed in a text, more specifically, the degree of subjectivity expressed in causal coherence relations. The main hypothesis is that the distribution of Dutch backward causal connectives (want, omdat, aangezien, and doordat) can be explained by the…

  19. Nonparametric causal inference for bivariate time series

    NASA Astrophysics Data System (ADS)

    McCracken, James M.; Weigel, Robert S.

    2016-02-01

    We introduce new quantities for exploratory causal inference between bivariate time series. The quantities, called penchants and leanings, are computationally straightforward to apply, follow directly from assumptions of probabilistic causality, do not depend on any assumed models for the time series generating process, and do not rely on any embedding procedures; these features may provide a clearer interpretation of the results than those from existing time series causality tools. The penchant and leaning are computed based on a structured method for computing probabilities.

  20. Causal inference in economics and marketing.

    PubMed

    Varian, Hal R

    2016-07-01

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144

  1. Causal inference in economics and marketing

    PubMed Central

    Varian, Hal R.

    2016-01-01

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144

  2. A causal model of adolescent depression.

    PubMed

    Brage, D; Meredith, W

    1994-07-01

    We examined how family strengths, parent-adolescent communication, self-esteem, loneliness, age, and gender interrelate, and how this interaction influences depression in adolescents. The data were collected on a written questionnaire completed by 156 adolescents who were attending public schools in four communities in the midwestern United States. We developed a causal model to explicate the relationships among the variables hypothesized to affect adolescent depression and analyzed the data using path analysis via the LISREL VII program. Results showed a good fit of the model to the data. Loneliness and self-esteem had a direct effect on adolescent depression. Self-esteem had an indirect effect on depression through loneliness. Age directly and indirectly influenced depression through loneliness. Gender was significantly related to depression through self-esteem. Family strengths indirectly affected depression through self-esteem. PMID:7932297

  3. Causal compensated perturbations in cosmology

    NASA Technical Reports Server (NTRS)

    Veeraraghavan, Shoba; Stebbins, Albert

    1990-01-01

    A theoretical framework is developed to calculate linear perturbations in the gravitational and matter fields which arise causally in response to the presence of stiff matter sources in a FRW cosmology. It is shown that, in order to satisfy energy and momentum conservation, the gravitational fields of the source must be compensated by perturbations in the matter and gravitational fields, and the role of such compensation in containing the initial inhomogeneities in their subsequent evolution is discussed. A complete formal solution is derived in terms of Green functions for the perturbations produced by an arbitrary source in a flat universe containing cold dark matter. Approximate Green function solutions are derived for the late-time density perturbations and late-time gravitational waves in a universe containing a radiation fluid. A cosmological energy-momentum pseudotensor is defined to clarify the nature of energy and momentum conservation in the expanding universe.

  4. Causality from the Cosmological Perspective in Vedanta and Western Physics.

    NASA Astrophysics Data System (ADS)

    Hawley, Danny Lee

    The relation between Western physics and Indian Vedanta philosophy is investigated through the topic of causality, taken in the sense of explanatory theories of the origin of the universe and the relations among its physical, mental, and spiritual aspects. Both physics and Vedanta have a common goal of explanation by means of a unitary principle. While physics has long been separated from metaphysics, its discoveries indicate that consciousness must be included in a complete explanation. Consciousness is taken as the fundamental basis and source of all phenomena in Vedanta. This work traces the developments of causal explanation in Western physics and Indian philosophy, and considers how these views may relate to each other and how they may together suggest a comprehensive view of reality. Approaches typically applied by historians of religion to the study of creation myths, especially the psychological approach which considers myths from the perspective or cyclical stages of conscious development, are applied to the causal theories of the two cultures. The question of how causal explanations attempt to bridge the gap between cause and effect, unity and multiplicity, absolute and relative, conscious and unconscious, etc., is addressed. Though the investigation begins from the earliest causal explanations, viz., creation myths, emphasis is placed upon Samkara's commentaries of Advaita Vedanta, examined in the original Sanskrit, and upon the convergence of modern field theory, astrophysics, and cosmology, seen from the perspective of a previous doctorate in physics. Consideration is given to the comparison between physics and Vedanta as to goals, methods, and domains, to the question of the incompleteness of physics and the extent to which it nevertheless points beyond itself, to the possibility of a synthetic view and how it might be effected, and to analogies and metaphors through which physics and Vedanta may illuminate each other. An intuitive picture is

  5. Causal Systems Categories: Differences in Novice and Expert Categorization of Causal Phenomena

    ERIC Educational Resources Information Center

    Rottman, Benjamin M.; Gentner, Dedre; Goldwater, Micah B.

    2012-01-01

    We investigated the understanding of causal systems categories--categories defined by common causal structure rather than by common domain content--among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative…

  6. Knowing Who Dunnit: Infants Identify the Causal Agent in an Unseen Causal Interaction

    ERIC Educational Resources Information Center

    Saxe, Rebecca; Tzelnic, Tania; Carey, Susan

    2007-01-01

    Preverbal infants can represent the causal structure of events, including distinguishing the agentive and receptive roles and categorizing entities according to stable causal dispositions. This study investigated how infants combine these 2 kinds of causal inference. In Experiments 1 and 2, 9.5-month-olds used the position of a human hand or a…

  7. Causality and stability of cosmic jets

    NASA Astrophysics Data System (ADS)

    Porth, Oliver; Komissarov, Serguei S.

    2015-09-01

    In stark contrast to their laboratory and terrestrial counterparts, cosmic jets appear to be very stable. They are able to penetrate vast spaces, which exceed by up to a billion times the size of their central engines. We propose that the reason behind this remarkable property is the loss of causal connectivity across these jets, caused by their rapid expansion in response to fast decline of external pressure with the distance from the `jet engine'. In atmospheres with power-law pressure distribution, pext ∝ z-κ, the total loss of causal connectivity occurs, when κ > 2 - the steepness which is expected to be quite common for many astrophysical environments. This conclusion does not seem to depend on the physical nature of jets - it applies both to relativistic and non-relativistic flows, both magnetically dominated and unmagnetized jets. In order to verify it, we have carried out numerical simulations of moderately magnetized and moderately relativistic jets. The results give strong support to our hypothesis and provide with valuable insights. In particular, we find that the z-pinched inner cores of magnetic jets expand slower than their envelopes and become susceptible to instabilities even when the whole jet is stable. This may result in local dissipation and emission without global disintegration of the flow. Cosmic jets may become globally unstable when they enter flat sections of external atmospheres. We propose that the Fanaroff-Riley (FR) morphological division of extragalactic radio sources into two classes is related to this issue. In particular, we argue that the low power FR-I jets become reconfined, causally connected and globally unstable on the scale of galactic X-ray coronas, whereas more powerful FR-II jets reconfine much further out, already on the scale of radio lobes and remain largely intact until they terminate at hotspots. Using this idea, we derived the relationship between the critical jet power and the optical luminosity of the host

  8. Causality and Cointegration Analysis between Macroeconomic Variables and the Bovespa

    PubMed Central

    da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

    2014-01-01

    The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelth month, followed by the country risk, with less than 5%. PMID:24587019

  9. Causality and cointegration analysis between macroeconomic variables and the Bovespa.

    PubMed

    da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

    2014-01-01

    The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%. PMID:24587019

  10. Determining Directional Dependency in Causal Associations

    ERIC Educational Resources Information Center

    Pornprasertmanit, Sunthud; Little, Todd D.

    2012-01-01

    Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of…

  11. Updating during Reading Comprehension: Why Causality Matters

    ERIC Educational Resources Information Center

    Kendeou, Panayiota; Smith, Emily R.; O'Brien, Edward J.

    2013-01-01

    The present set of 7 experiments systematically examined the effectiveness of adding causal explanations to simple refutations in reducing or eliminating the impact of outdated information on subsequent comprehension. The addition of a single causal-explanation sentence to a refutation was sufficient to eliminate any measurable disruption in…

  12. Making the Case for Causal Dynamical Triangulations

    NASA Astrophysics Data System (ADS)

    Cooperman, Joshua H.

    2015-11-01

    The aim of the causal dynamical triangulations approach is to define nonperturbatively a quantum theory of gravity as the continuum limit of a lattice-regularized model of dynamical geometry. My aim in this paper is to give a concise yet comprehensive, impartial yet personal presentation of the causal dynamical triangulations approach.

  13. Controlling for causally relevant third variables.

    PubMed

    Goodie, Adam S; Williams, Cristina C; Crooks, C L

    2003-10-01

    In 3 experiments, the authors tested the conditions under which 3rd variables are controlled for in making causal judgments. The authors hypothesized that 3rd variables are controlled for when the 3rd variables are themselves perceived as causal. In Experiment 1, the participants predicted test performance after seeing information about wearing a lucky garment, taking a test-preparation course, and staying up late. The course (perceived as more causally relevant) was controlled for more than was the garment (perceived as less causally relevant) in assessing the effectiveness of staying up late. In Experiments 2 and 3, to obviate the many alternative accounts that arise from the realistic cover story of Experiment 1, participants predicted flowers' blooming after the presentation or nonpresentation of liquids. When one liquid was trained as causal, it was controlled for more in judging another liquid than when it was trained as neutral. Overall, stimuli perceived as causal were controlled for more when judging other stimuli. The authors concluded that the effect of perceived causal relevance on causal conditionalizing is real and normatively reasonable. PMID:14672103

  14. Inference and Action in Early Causal Reasoning.

    ERIC Educational Resources Information Center

    Frye, Douglas; And Others

    1996-01-01

    Two marble-and-ramp experiments investigated whether a simple-to-embedded-rules account can explain changes in children's causal reasoning. Results indicated that the same difference between three- and four-year olds in the prediction experiment appeared in the action experiment, suggesting that the same rules may underlie causal action as well as…

  15. A Causal Model of Faculty Research Productivity.

    ERIC Educational Resources Information Center

    Bean, John P.

    A causal model of faculty research productivity was developed through a survey of the literature. Models of organizational behavior, organizational effectiveness, and motivation were synthesized into a causal model of productivity. Two general types of variables were assumed to affect individual research productivity: institutional variables and…

  16. Compact Representations of Extended Causal Models

    ERIC Educational Resources Information Center

    Halpern, Joseph Y.; Hitchcock, Christopher

    2013-01-01

    Judea Pearl (2000) was the first to propose a definition of actual causation using causal models. A number of authors have suggested that an adequate account of actual causation must appeal not only to causal structure but also to considerations of "normality." In Halpern and Hitchcock (2011), we offer a definition of actual causation…

  17. A General Approach to Causal Mediation Analysis

    ERIC Educational Resources Information Center

    Imai, Kosuke; Keele, Luke; Tingley, Dustin

    2010-01-01

    Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…

  18. Causal Mediation Analysis: Warning! Assumptions Ahead

    ERIC Educational Resources Information Center

    Keele, Luke

    2015-01-01

    In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…

  19. The Acquisition of Causal Connectives in Turkish.

    ERIC Educational Resources Information Center

    Aksu, Ayhan

    The elicited speech of 26 Turkish children ranging in age from 2;0 to 4;6 was examined with respect to causality. The developmental sequence of the acquisition of causal connectives showed a progression from the use of no explicit connectives to the acquisition of connectives that are context-dependent. The next stage in this progression was the…

  20. Causal Inferences during Text Comprehension and Production.

    ERIC Educational Resources Information Center

    Kemper, Susan

    As comprehension failure results whenever readers are unable to infer missing causal connections, recent comprehension research has focused both on assessing the inferential complexity of texts and on investigating students' developing ability to infer causal relationships. Studies have demonstrated that texts rely on four types of causal…

  1. Campbell's and Rubin's Perspectives on Causal Inference

    ERIC Educational Resources Information Center

    West, Stephen G.; Thoemmes, Felix

    2010-01-01

    Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…

  2. Granger causality for state-space models

    NASA Astrophysics Data System (ADS)

    Barnett, Lionel; Seth, Anil K.

    2015-04-01

    Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

  3. Causal Inferences in the Campbellian Validity System

    ERIC Educational Resources Information Center

    Lund, Thorleif

    2010-01-01

    The purpose of the present paper is to critically examine causal inferences and internal validity as defined by Campbell and co-workers. Several arguments are given against their counterfactual effect definition, and this effect definition should be considered inadequate for causal research in general. Moreover, their defined independence between…

  4. Essays on Causal Inference for Public Policy

    ERIC Educational Resources Information Center

    Zajonc, Tristan

    2012-01-01

    Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…

  5. Confounding Effects of Phase Delays on Causality Estimation

    PubMed Central

    Vakorin, Vasily A.; Mišić, Bratislav; Krakovska, Olga; Bezgin, Gleb; McIntosh, Anthony R.

    2013-01-01

    Linear and non-linear techniques for inferring causal relations between the brain signals representing the underlying neuronal systems have become a powerful tool to extract the connectivity patterns in the brain. Typically these tools employ the idea of Granger causality, which is ultimately based on the temporal precedence between the signals. At the same time, phase synchronization between coupled neural ensembles is considered a mechanism implemented in the brain to integrate relevant neuronal ensembles to perform a cognitive or perceptual task. Phase synchronization can be studied by analyzing the effects of phase-locking between the brain signals. However, we should expect that there is no one-to-one mapping between the observed phase lag and the time precedence as specified by physically interacting systems. Specifically, phase lag observed between two signals may interfere with inferring causal relations. This could be of critical importance for the coupled non-linear oscillating systems, with possible time delays in coupling, when classical linear cross-spectrum strategies for solving phase ambiguity are not efficient. To demonstrate this, we used a prototypical model of coupled non-linear systems, and compared three typical pipelines of inferring Granger causality, as established in the literature. Specifically, we compared the performance of the spectral and information-theoretic Granger pipelines as well as standard Granger causality in their relations to the observed phase differences for frequencies at which the signals become synchronized to each other. We found that an information-theoretic approach, which takes into account different time lags between the past of one signal and the future of another signal, was the most robust to phase effects. PMID:23349720

  6. Recursive partitioning for heterogeneous causal effects.

    PubMed

    Athey, Susan; Imbens, Guido

    2016-07-01

    In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals for treatment effects, even with many covariates relative to the sample size, and without "sparsity" assumptions. We propose an "honest" approach to estimation, whereby one sample is used to construct the partition and another to estimate treatment effects for each subpopulation. Our approach builds on regression tree methods, modified to optimize for goodness of fit in treatment effects and to account for honest estimation. Our model selection criterion anticipates that bias will be eliminated by honest estimation and also accounts for the effect of making additional splits on the variance of treatment effect estimates within each subpopulation. We address the challenge that the "ground truth" for a causal effect is not observed for any individual unit, so that standard approaches to cross-validation must be modified. Through a simulation study, we show that for our preferred method honest estimation results in nominal coverage for 90% confidence intervals, whereas coverage ranges between 74% and 84% for nonhonest approaches. Honest estimation requires estimating the model with a smaller sample size; the cost in terms of mean squared error of treatment effects for our preferred method ranges between 7-22%. PMID:27382149

  7. Recursive partitioning for heterogeneous causal effects

    PubMed Central

    Athey, Susan; Imbens, Guido

    2016-01-01

    In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals for treatment effects, even with many covariates relative to the sample size, and without “sparsity” assumptions. We propose an “honest” approach to estimation, whereby one sample is used to construct the partition and another to estimate treatment effects for each subpopulation. Our approach builds on regression tree methods, modified to optimize for goodness of fit in treatment effects and to account for honest estimation. Our model selection criterion anticipates that bias will be eliminated by honest estimation and also accounts for the effect of making additional splits on the variance of treatment effect estimates within each subpopulation. We address the challenge that the “ground truth” for a causal effect is not observed for any individual unit, so that standard approaches to cross-validation must be modified. Through a simulation study, we show that for our preferred method honest estimation results in nominal coverage for 90% confidence intervals, whereas coverage ranges between 74% and 84% for nonhonest approaches. Honest estimation requires estimating the model with a smaller sample size; the cost in terms of mean squared error of treatment effects for our preferred method ranges between 7–22%. PMID:27382149

  8. Discovering phenotypic causal structure from nonexperimental data.

    PubMed

    Otsuka, J

    2016-06-01

    The evolutionary potential of organisms depends on how their parts are structured into a cohesive whole. A major obstacle for empirical studies of phenotypic organization is that observed associations among characters usually confound different causal pathways such as pleiotropic modules, interphenotypic causal relationships and environmental effects. The present article proposes causal search algorithms as a new tool to distinguish these different modes of phenotypic integration. Without assuming an a priori structure, the algorithms seek a class of causal hypotheses consistent with independence relationships holding in observational data. The technique can be applied to discover causal relationships among a set of measured traits and to distinguish genuine selection from spurious correlations. The former application is illustrated with a biological data set of rat morphological measurements previously analysed by Cheverud et al. (Evolution 1983, 37, 895). PMID:27007864

  9. Causal Supports for Early Word Learning

    PubMed Central

    Booth, Amy E.

    2009-01-01

    What factors determine whether a young child will learn a new word? Although there are surely numerous contributors, the current investigation highlights the role of causal information. Thirty-six 3-year-old children were taught 6 new words for unfamiliar objects or animals. Items were described in terms of their causal or non-causal properties. When tested only minutes after training, no significant differences between the conditions were evident. However, when tested several days after training, children performed better on words trained in the causal condition. These results demonstrate that the well-documented effect of causal information on learning and categorization extends to word learning in young children. PMID:19630905

  10. Causality, Bell's theorem, and Ontic Definiteness

    NASA Astrophysics Data System (ADS)

    Henson, Joe

    2011-03-01

    Bell's theorem shows that the reasonable relativistic causal principle known as ``local causality'' is not compatible with the predictions of quantum mechanics. It is not possible maintain a satisfying causal principle of this type while dropping any of the better-known assumptions of Bell's theorem. However, another assumption of Bell's theorem is the use of classical logic. One part of this assumption is the principle of ontic definiteness, that is, that it must in principle be possible to assign definite truth values to all propositions treated in the theory. Once the logical setting is clarified somewhat, it can be seen that rejecting this principle does not in any way undermine the type of causal principle used by Bell. Without ontic definiteness, the deterministic causal condition known as Einstein Locality succeeds in banning superluminal influence (including signalling) whilst allowing correlations that violate Bell's inequalities. Objections to altering logic, and the consequences for operational and realistic viewpoints, are also addressed.

  11. Causal effects in psychotherapy: counterfactuals counteract overgeneralization.

    PubMed

    Hofler, Michael; Gloster, Andrew T; Hoyer, Jurgen

    2010-11-01

    Causal inference of psychotherapy effects is usually based on the theory of internal and external validity. The authors argue that as an inductive strategy it often leads to overgeneralization because it promotes neglect of specific clinical boundary conditions (such as practically relevant combinations of treatments, settings, patients, and therapists). Adding the counterfactual conceptualization of causal effects counteracts overgeneralization by considering individuals at a fixed time under two possible treatment conditions as basic units of a causal effect. Consequently, causal effects are regarded as varying in nature as local pieces of a global theory. The authors outline the main deductions from the counterfactual conceptualization with regard to understanding causality, average effects, bias, and study design and address some controversies in psychotherapy research. PMID:20924977

  12. Electrophysiological difference between the representations of causal judgment and associative judgment in semantic memory.

    PubMed

    Chen, Qingfei; Liang, Xiuling; Lei, Yi; Li, Hong

    2015-05-01

    Causally related concepts like "virus" and "epidemic" and general associatively related concepts like "ring" and "emerald" are represented and accessed separately. The Evoked Response Potential (ERP) procedure was used to examine the representations of causal judgment and associative judgment in semantic memory. Participants were required to remember a task cue (causal or associative) presented at the beginning of each trial, and assess whether the relationship between subsequently presented words matched the initial task cue. The ERP data showed that an N400 effect (250-450 ms) was more negative for unrelated words than for all related words. Furthermore, the N400 effect elicited by causal relations was more positive than for associative relations in causal cue condition, whereas no significant difference was found in the associative cue condition. The centrally distributed late ERP component (650-750 ms) elicited by the causal cue condition was more positive than for the associative cue condition. These results suggested that the processing of causal judgment and associative judgment in semantic memory recruited different degrees of attentional and executive resources. PMID:25813899

  13. Illusions of causality: how they bias our everyday thinking and how they could be reduced.

    PubMed

    Matute, Helena; Blanco, Fernando; Yarritu, Ion; Díaz-Lago, Marcos; Vadillo, Miguel A; Barberia, Itxaso

    2015-01-01

    Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion. PMID:26191014

  14. Complex Causal Process Diagrams for Analyzing the Health Impacts of Policy Interventions

    PubMed Central

    Joffe, Michael; Mindell, Jennifer

    2006-01-01

    Causal diagrams are rigorous tools for controlling confounding. They also can be used to describe complex causal systems, which is done routinely in communicable disease epidemiology. The use of change diagrams has advantages over static diagrams, because change diagrams are more tractable, relate better to interventions, and have clearer interpretations. Causal diagrams are a useful basis for modeling. They make assumptions explicit, provide a framework for analysis, generate testable predictions, explore the effects of interventions, and identify data gaps. Causal diagrams can be used to integrate different types of information and to facilitate communication both among public health experts and between public health experts and experts in other fields. Causal diagrams allow the use of instrumental variables, which can help control confounding and reverse causation. PMID:16449586

  15. Property transmission: an explanatory account of the role of similarity information in causal inference.

    PubMed

    White, Peter A

    2009-09-01

    Many kinds of common and easily observed causal relations exhibit property transmission, which is a tendency for the causal object to impose its own properties on the effect object. It is proposed that property transmission becomes a general and readily available hypothesis used to make interpretations and judgments about causal questions under conditions of uncertainty, in which property transmission functions as a heuristic. The property transmission hypothesis explains why and when similarity information is used in causal inference. It can account for magical contagion beliefs, some cases of illusory correlation, the correspondence bias, overestimation of cross-situational consistency in behavior, nonregressive tendencies in prediction, the belief that acts of will are causes of behavior, and a range of other phenomena. People learn that property transmission is often moderated by other factors, but under conditions of uncertainty in which the operation of relevant other factors is unknown, it tends to exhibit a pervasive influence on thinking about causality. PMID:19702382

  16. Appearance of causality in process matrices when performing fixed-basis measurements for two parties

    NASA Astrophysics Data System (ADS)

    Baumann, Veronika; Brukner, Časlav

    2016-06-01

    The recently developed framework for quantum theory with no global causal order allows for quantum processes in which operations in local laboratories are neither causally ordered nor in a probabilistic mixture of definite causal orders. The causal relation between the laboratories is described by the process matrix. We show that, if the inputs of the laboratories are measured in a fixed basis, one can introduce an effective process matrix which is operationally indistinguishable from the original one. This effective process matrix can be obtained by applying the von Neumann-Lüders update rule for nonselective measurements to the original process matrix and, in the bipartite case, it is compatible with a definite causal order. The latter extends the original Oreshkov et al. proof where one considers that both the measurement of the input and the re-preparation of the output are performed in a fixed basis.

  17. Illusions of causality: how they bias our everyday thinking and how they could be reduced

    PubMed Central

    Matute, Helena; Blanco, Fernando; Yarritu, Ion; Díaz-Lago, Marcos; Vadillo, Miguel A.; Barberia, Itxaso

    2015-01-01

    Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion. PMID:26191014

  18. BioCause: Annotating and analysing causality in the biomedical domain

    PubMed Central

    2013-01-01

    Background Biomedical corpora annotated with event-level information represent an important resource for domain-specific information extraction (IE) systems. However, bio-event annotation alone cannot cater for all the needs of biologists. Unlike work on relation and event extraction, most of which focusses on specific events and named entities, we aim to build a comprehensive resource, covering all statements of causal association present in discourse. Causality lies at the heart of biomedical knowledge, such as diagnosis, pathology or systems biology, and, thus, automatic causality recognition can greatly reduce the human workload by suggesting possible causal connections and aiding in the curation of pathway models. A biomedical text corpus annotated with such relations is, hence, crucial for developing and evaluating biomedical text mining. Results We have defined an annotation scheme for enriching biomedical domain corpora with causality relations. This schema has subsequently been used to annotate 851 causal relations to form BioCause, a collection of 19 open-access full-text biomedical journal articles belonging to the subdomain of infectious diseases. These documents have been pre-annotated with named entity and event information in the context of previous shared tasks. We report an inter-annotator agreement rate of over 60% for triggers and of over 80% for arguments using an exact match constraint. These increase significantly using a relaxed match setting. Moreover, we analyse and describe the causality relations in BioCause from various points of view. This information can then be leveraged for the training of automatic causality detection systems. Conclusion Augmenting named entity and event annotations with information about causal discourse relations could benefit the development of more sophisticated IE systems. These will further influence the development of multiple tasks, such as enabling textual inference to detect entailments, discovering new

  19. Recognising discourse causality triggers in the biomedical domain.

    PubMed

    Mihăilă, Claudiu; Ananiadou, Sophia

    2013-12-01

    Current domain-specific information extraction systems represent an important resource for biomedical researchers, who need to process vast amounts of knowledge in a short time. Automatic discourse causality recognition can further reduce their workload by suggesting possible causal connections and aiding in the curation of pathway models. We describe here an approach to the automatic identification of discourse causality triggers in the biomedical domain using machine learning. We create several baselines and experiment with and compare various parameter settings for three algorithms, i.e. Conditional Random Fields (CRF), Support Vector Machines (SVM) and Random Forests (RF). We also evaluate the impact of lexical, syntactic, and semantic features on each of the algorithms, showing that semantics improves the performance in all cases. We test our comprehensive feature set on two corpora containing gold standard annotations of causal relations, and demonstrate the need for more gold standard data. The best performance of 79.35% F-score is achieved by CRFs when using all three feature types. PMID:24372037

  20. Spread of entanglement and causality

    NASA Astrophysics Data System (ADS)

    Casini, Horacio; Liu, Hong; Mezei, Márk

    2016-07-01

    We investigate causality constraints on the time evolution of entanglement entropy after a global quench in relativistic theories. We first provide a general proof that the so-called tsunami velocity is bounded by the speed of light. We then generalize the free particle streaming model of [1] to general dimensions and to an arbitrary entanglement pattern of the initial state. In more than two spacetime dimensions the spread of entanglement in these models is highly sensitive to the initial entanglement pattern, but we are able to prove an upper bound on the normalized rate of growth of entanglement entropy, and hence the tsunami velocity. The bound is smaller than what one gets for quenches in holographic theories, which highlights the importance of interactions in the spread of entanglement in many-body systems. We propose an interacting model which we believe provides an upper bound on the spread of entanglement for interacting relativistic theories. In two spacetime dimensions with multiple intervals, this model and its variations are able to reproduce intricate results exhibited by holographic theories for a significant part of the parameter space. For higher dimensions, the model bounds the tsunami velocity at the speed of light. Finally, we construct a geometric model for entanglement propagation based on a tensor network construction for global quenches.

  1. What is the nature of causality in the brain? - Inherently probabilistic. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

    NASA Astrophysics Data System (ADS)

    Dhamala, Mukesh

    2015-12-01

    Understanding cause-and-effect (causal) relations from observations concerns all sciences including neuroscience. Appropriately defining causality and its nature, though, has been a topic of active discussion for philosophers and scientists for centuries. Although brain research, particularly functional neuroimaging research, is now moving rapidly beyond identification of brain regional activations towards uncovering causal relations between regions, the nature of causality has not be been thoroughly described and resolved. In the current review article [1], Mannino and Bressler take us on a beautiful journey into the history of the work on causality and make a well-reasoned argument that the causality in the brain is inherently probabilistic. This notion is consistent with brain anatomy and functions, and is also inclusive of deterministic cases of inputs leading to outputs in the brain.

  2. Quantum correlations with no causal order

    PubMed Central

    Oreshkov, Ognyan; Costa, Fabio; Brukner, Časlav

    2012-01-01

    The idea that events obey a definite causal order is deeply rooted in our understanding of the world and at the basis of the very notion of time. But where does causal order come from, and is it a necessary property of nature? Here, we address these questions from the standpoint of quantum mechanics in a new framework for multipartite correlations that does not assume a pre-defined global causal structure but only the validity of quantum mechanics locally. All known situations that respect causal order, including space-like and time-like separated experiments, are captured by this framework in a unified way. Surprisingly, we find correlations that cannot be understood in terms of definite causal order. These correlations violate a 'causal inequality' that is satisfied by all space-like and time-like correlations. We further show that in a classical limit causal order always arises, which suggests that space-time may emerge from a more fundamental structure in a quantum-to-classical transition. PMID:23033068

  3. Causal discovery via reproducing kernel Hilbert space embeddings.

    PubMed

    Chen, Zhitang; Zhang, Kun; Chan, Laiwan; Schölkopf, Bernhard

    2014-07-01

    Causal discovery via the asymmetry between the cause and the effect has proved to be a promising way to infer the causal direction from observations. The basic idea is to assume that the mechanism generating the cause distribution p(x) and that generating the conditional distribution p(y|x) correspond to two independent natural processes and thus p(x) and p(y|x) fulfill some sort of independence condition. However, in many situations, the independence condition does not hold for the anticausal direction; if we consider p(x, y) as generated via p(y)p(x|y), then there are usually some contrived mutual adjustments between p(y) and p(x|y). This kind of asymmetry can be exploited to identify the causal direction. Based on this postulate, in this letter, we define an uncorrelatedness criterion between p(x) and p(y|x) and, based on this uncorrelatedness, show asymmetry between the cause and the effect in terms that a certain complexity metric on p(x) and p(y|x) is less than the complexity metric on p(y) and p(x|y). We propose a Hilbert space embedding-based method EMD (an abbreviation for EMbeDding) to calculate the complexity metric and show that this method preserves the relative magnitude of the complexity metric. Based on the complexity metric, we propose an efficient kernel-based algorithm for causal discovery. The contribution of this letter is threefold. It allows a general transformation from the cause to the effect involving the noise effect and is applicable to both one-dimensional and high-dimensional data. Furthermore it can be used to infer the causal ordering for multiple variables. Extensive experiments on simulated and real-world data are conducted to show the effectiveness of the proposed method. PMID:24708374

  4. Reward-Guided Learning with and without Causal Attribution.

    PubMed

    Jocham, Gerhard; Brodersen, Kay H; Constantinescu, Alexandra O; Kahn, Martin C; Ianni, Angela M; Walton, Mark E; Rushworth, Matthew F S; Behrens, Timothy E J

    2016-04-01

    When an organism receives a reward, it is crucial to know which of many candidate actions caused this reward. However, recent work suggests that learning is possible even when this most fundamental assumption is not met. We used novel reward-guided learning paradigms in two fMRI studies to show that humans deploy separable learning mechanisms that operate in parallel. While behavior was dominated by precise contingent learning, it also revealed hallmarks of noncontingent learning strategies. These learning mechanisms were separable behaviorally and neurally. Lateral orbitofrontal cortex supported contingent learning and reflected contingencies between outcomes and their causal choices. Amygdala responses around reward times related to statistical patterns of learning. Time-based heuristic mechanisms were related to activity in sensorimotor corticostriatal circuitry. Our data point to the existence of several learning mechanisms in the human brain, of which only one relies on applying known rules about the causal structure of the task. PMID:26971947

  5. Reward-Guided Learning with and without Causal Attribution

    PubMed Central

    Jocham, Gerhard; Brodersen, Kay H.; Constantinescu, Alexandra O.; Kahn, Martin C.; Ianni, Angela M.; Walton, Mark E.; Rushworth, Matthew F.S.; Behrens, Timothy E.J.

    2016-01-01

    Summary When an organism receives a reward, it is crucial to know which of many candidate actions caused this reward. However, recent work suggests that learning is possible even when this most fundamental assumption is not met. We used novel reward-guided learning paradigms in two fMRI studies to show that humans deploy separable learning mechanisms that operate in parallel. While behavior was dominated by precise contingent learning, it also revealed hallmarks of noncontingent learning strategies. These learning mechanisms were separable behaviorally and neurally. Lateral orbitofrontal cortex supported contingent learning and reflected contingencies between outcomes and their causal choices. Amygdala responses around reward times related to statistical patterns of learning. Time-based heuristic mechanisms were related to activity in sensorimotor corticostriatal circuitry. Our data point to the existence of several learning mechanisms in the human brain, of which only one relies on applying known rules about the causal structure of the task. PMID:26971947

  6. Granger-causality maps of diffusion processes

    NASA Astrophysics Data System (ADS)

    Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A.

    2016-02-01

    Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.

  7. Effective connectivity: Influence, causality and biophysical modeling

    PubMed Central

    Valdes-Sosa, Pedro A.; Roebroeck, Alard; Daunizeau, Jean; Friston, Karl

    2011-01-01

    This is the final paper in a Comments and Controversies series dedicated to “The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution”. We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of Bayesian dependency graphs and Wiener–Akaike–Granger–Schweder influence measures. We show that some of the challenges faced in this field have promising solutions and speculate on future developments. PMID:21477655

  8. Causal learning about tolerance and sensitization

    PubMed Central

    Rottman, Benjamin Margolin; Ahn, Woo-kyoung

    2010-01-01

    We introduce two abstract, causal schemata used during causal learning. (1) Tolerance is when an effect diminishes over time, as an entity is repeatedly exposed to the cause (e.g., a person becoming tolerant to caffeine). (2) Sensitization is when an effect intensifies over time, as an entity is repeatedly exposed to the cause (e.g., an antidepressant becoming more effective through repeated use). In Experiment 1, participants observed either of these cause–effect data patterns unfolding over time and exhibiting the tolerance or sensitization schemata. Participants inferred stronger causal efficacy and made more confident and more extreme predictions about novel cases than in a condition with the same data appearing in a random order over time. In Experiment 2, the same tolerance/sensitization scenarios occurred either within one entity or across many entities. In the many-entity conditions, when the schemata were violated, participants made much weaker inferences. Implications for causal learning are discussed. PMID:19966253

  9. Quantum probability assignment limited by relativistic causality.

    PubMed

    Han, Yeong Deok; Choi, Taeseung

    2016-01-01

    Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717

  10. Granger-causality maps of diffusion processes.

    PubMed

    Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A

    2016-02-01

    Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes. PMID:26986337

  11. Quantum probability assignment limited by relativistic causality

    PubMed Central

    Han, Yeong Deok; Choi, Taeseung

    2016-01-01

    Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717

  12. Vitalistic causality in young children's naive biology.

    PubMed

    Inagaki, Kayoko; Hatano, Giyoo

    2004-08-01

    One of the key issues in conceptual development research concerns what kinds of causal devices young children use to understand the biological world. We review evidence that children predict and interpret biological phenomena, especially human bodily processes, on the basis of 'vitalistic causality'. That is, they assume that vital power or life force taken from food and water makes humans active, prevents them from being taken ill, and enables them to grow. These relationships are also extended readily to other animals and even to plants. Recent experimental results show that a majority of preschoolers tend to choose vitalistic explanations as most plausible. Vitalism, together with other forms of intermediate causality, constitute unique causal devices for naive biology as a core domain of thought. PMID:15335462

  13. Linking and Causality in Globally Hyperbolic Space-times

    NASA Astrophysics Data System (ADS)

    Chernov (Tchernov), Vladimir V.; Rudyak, Yuli B.

    2008-04-01

    The classical linking number lk is defined when link components are zero homologous. In [15] we constructed the affine linking invariant alk generalizing lk to the case of linked submanifolds with arbitrary homology classes. Here we apply alk to the study of causality in Lorentzian manifolds. Let M m be a spacelike Cauchy surface in a globally hyperbolic space-time ( X m+1, g). The spherical cotangent bundle ST * M is identified with the space mathcal N of all null geodesics in ( X, g). Hence the set of null geodesics passing through a point xin X gives an embedded ( m-1)-sphere mathfrak S_x in mathcal N=ST^*M called the sky of x. Low observed that if the link (mathfrak S_x, mathfrak S_y) is nontrivial, then x,yin X are causally related. This observation yielded a problem (communicated by R. Penrose) on the V. I. Arnold problem list [3,4] which is basically to study the relation between causality and linking. Our paper is motivated by this question. The spheres mathfrak S_x are isotopic to the fibers of (ST^*M)^{2m-1}to M^m. They are nonzero homologous and the classical linking number lk(mathfrak S_x, mathfrak S_y) is undefined when M is closed, while alk(mathfrak S_x, mathfrak S_y) is well defined. Moreover, alk(mathfrak S_x, mathfrak S_y)in {mathbb{Z}} if M is not an odd-dimensional rational homology sphere. We give a formula for the increment of alk under passages through Arnold dangerous tangencies. If ( X, g) is such that alk takes values in {mathbb{Z}} and g is conformal to widehat{g} that has all the timelike sectional curvatures nonnegative, then x, yin X are causally related if and only if alk (mathfrak S_x, mathfrak S_y)neq 0 . We prove that if alk takes values in {mathbb{Z}} and y is in the causal future of x, then alk(mathfrak S_x, mathfrak S_y) is the intersection number of any future directed past inextendible timelike curve to y and of the future null cone of x. We show that x, y in a nonrefocussing ( X, g) are causally unrelated if and only if

  14. Causality violation, gravitational shockwaves and UV completion

    NASA Astrophysics Data System (ADS)

    Hollowood, Timothy J.; Shore, Graham M.

    2016-03-01

    The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of "time machines", i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate how the resulting causality problems emerge and are resolved in a two-shockwave time machine scenario. The implications of our results for ultra-high (Planck) energy scattering, in which graviton exchange is modelled by the shockwave background, are highlighted.

  15. Associative foundation of causal learning in rats.

    PubMed

    Polack, Cody W; McConnell, Bridget L; Miller, Ralph R

    2013-03-01

    Are humans unique in their ability to interpret exogenous events as causes? We addressed this question by observing the behavior of rats for indications of causal learning. Within an operant motor-sensory preconditioning paradigm, associative surgical techniques revealed that rats attempted to control an outcome (i.e., a potential effect) by manipulating a potential exogenous cause (i.e., an intervention). Rats were able to generate an innocuous auditory stimulus. This stimulus was then paired with an aversive stimulus. The animals subsequently avoided potential generation of the predictive cue, but not if the aversive stimulus was subsequently devalued or the predictive cue was extinguished (Exp. 1). In Experiment 2, we demonstrated that the aversive stimulus we used was in fact aversive, that it was subject to devaluation, that the cue-aversive stimulus pairings did make the cue a conditioned stimulus, and that the cue was subject to extinction. In Experiments 3 and 4, we established that the decrease in leverpressing observed in Experiment 1 was goal-directed instrumental behavior rather than purely a product of Pavlovian conditioning. To the extent that interventions suggest causal reasoning, it appears that causal reasoning can be based on associations between contiguous exogenous events. Thus, contiguity appears capable of establishing causal relationships between exogenous events. Our results challenge the widely held view that causal learning is uniquely human, and suggest that causal learning is explicable in an associative framework. PMID:22562460

  16. Dynamic causal models and autopoietic systems.

    PubMed

    David, Olivier

    2007-01-01

    Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681

  17. Research designs and making causal inferences from health care studies.

    PubMed

    Flannelly, Kevin J; Jankowski, Katherine R B

    2014-01-01

    This article summarizes the major types of research designs used in healthcare research, including experimental, quasi-experimental, and observational studies. Observational studies are divided into survey studies (descriptive and correlational studies), case-studies and analytic studies, the last of which are commonly used in epidemiology: case-control, retrospective cohort, and prospective cohort studies. Similarities and differences among the research designs are described and the relative strength of evidence they provide is discussed. Emphasis is placed on five criteria for drawing causal inferences that are derived from the writings of the philosopher John Stuart Mill, especially his methods or canons. The application of the criteria to experimentation is explained. Particular attention is given to the degree to which different designs meet the five criteria for making causal inferences. Examples of specific studies that have used various designs in chaplaincy research are provided. PMID:24579956

  18. Causality as individual essence: its bearing on synchronicity.

    PubMed

    Tougas, Cecile T

    2014-06-01

    Causality, time, and number are subjectively lived realities and need to be noticed as such. Fundamental to the wide range of living experience, they are also basic to scientific knowing. In this article I examine causality in relation to an article on synchronicity by Harald Atmanspacher and Wolfgang Fach. My examination is neither scientific nor metaphysical, but rather phenomenological, as it is a clarification of form as individual essence of a thing. This non-material form of an individual thing in the widest sense of the word 'thing' was rejected and so lost during modern seventeenth-century science but, renewed now, can help describe synchronicity. A commentary by William Willeford follows. PMID:24919632

  19. Quantifying information transfer and mediation along causal pathways in complex systems

    NASA Astrophysics Data System (ADS)

    Runge, Jakob

    2015-12-01

    Measures of information transfer have become a popular approach to analyze interactions in complex systems such as the Earth or the human brain from measured time series. Recent work has focused on causal definitions of information transfer aimed at decompositions of predictive information about a target variable, while excluding effects of common drivers and indirect influences. While common drivers clearly constitute a spurious causality, the aim of the present article is to develop measures quantifying different notions of the strength of information transfer along indirect causal paths, based on first reconstructing the multivariate causal network. Another class of novel measures quantifies to what extent different intermediate processes on causal paths contribute to an interaction mechanism to determine pathways of causal information transfer. The proposed framework complements predictive decomposition schemes by focusing more on the interaction mechanism between multiple processes. A rigorous mathematical framework allows for a clear information-theoretic interpretation that can also be related to the underlying dynamics as proven for certain classes of processes. Generally, however, estimates of information transfer remain hard to interpret for nonlinearly intertwined complex systems. But if experiments or mathematical models are not available, then measuring pathways of information transfer within the causal dependency structure allows at least for an abstraction of the dynamics. The measures are illustrated on a climatological example to disentangle pathways of atmospheric flow over Europe.

  20. Visual Causal Models Enhance Clinical Explanations of Treatments for Generalized Anxiety Disorder

    PubMed Central

    Kim, Nancy S.; Khalife, Danielle; Judge, Kelly A.; Paulus, Daniel J.; Jordan, Jake T.; Yopchick, Jennelle E.

    2013-01-01

    A daily challenge in clinical practice is to adequately explain disorders and treatments to patients of varying levels of literacy in a time-limited situation. Drawing jointly upon research on causal reasoning and multimodal theory, the authors asked whether adding visual causal models to clinical explanations promotes patient learning. Participants were 86 people currently or formerly diagnosed with a mood disorder and 104 lay people in Boston, Massachusetts, USA, who were randomly assigned to receive either a visual causal model (dual-mode) presentation or auditory-only presentation of an explanation about generalized anxiety disorder and its treatment. Participants' knowledge was tested before, immediately after, and 4 weeks after the presentation. Patients and lay people learned significantly more from visual causal model presentations than from auditory-only presentations, and visual causal models were perceived to be helpful. Participants retained some information 4 weeks after the presentation, although the advantage of visual causal models did not persist in the long term. In conclusion, dual-mode presentations featuring visual causal models yield significant relative gains in patient comprehension immediately after the clinical session, at a time when the authors suggest that patients may be most willing to begin the recommended treatment plan. PMID:24093349

  1. Quantifying information transfer and mediation along causal pathways in complex systems.

    PubMed

    Runge, Jakob

    2015-12-01

    Measures of information transfer have become a popular approach to analyze interactions in complex systems such as the Earth or the human brain from measured time series. Recent work has focused on causal definitions of information transfer aimed at decompositions of predictive information about a target variable, while excluding effects of common drivers and indirect influences. While common drivers clearly constitute a spurious causality, the aim of the present article is to develop measures quantifying different notions of the strength of information transfer along indirect causal paths, based on first reconstructing the multivariate causal network. Another class of novel measures quantifies to what extent different intermediate processes on causal paths contribute to an interaction mechanism to determine pathways of causal information transfer. The proposed framework complements predictive decomposition schemes by focusing more on the interaction mechanism between multiple processes. A rigorous mathematical framework allows for a clear information-theoretic interpretation that can also be related to the underlying dynamics as proven for certain classes of processes. Generally, however, estimates of information transfer remain hard to interpret for nonlinearly intertwined complex systems. But if experiments or mathematical models are not available, then measuring pathways of information transfer within the causal dependency structure allows at least for an abstraction of the dynamics. The measures are illustrated on a climatological example to disentangle pathways of atmospheric flow over Europe. PMID:26764766

  2. Singular Clues to Causality and Their Use in Human Causal Judgment

    ERIC Educational Resources Information Center

    White, Peter A.

    2014-01-01

    It is argued that causal understanding originates in experiences of acting on objects. Such experiences have consistent features that can be used as clues to causal identification and judgment. These are singular clues, meaning that they can be detected in single instances. A catalog of 14 singular clues is proposed. The clues function as…

  3. The Mental Representation of Causal Conditional Reasoning: Mental Models or Causal Models

    ERIC Educational Resources Information Center

    Ali, Nilufa; Chater, Nick; Oaksford, Mike

    2011-01-01

    In this paper, two experiments are reported investigating the nature of the cognitive representations underlying causal conditional reasoning performance. The predictions of causal and logical interpretations of the conditional diverge sharply when inferences involving "pairs" of conditionals--such as "if P[subscript 1] then Q" and "if P[subscript…

  4. The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality

    ERIC Educational Resources Information Center

    Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

    2013-01-01

    Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we…

  5. Preschoolers prefer to learn causal information

    PubMed Central

    Alvarez, Aubry L.; Booth, Amy E.

    2015-01-01

    Young children, in general, appear to have a strong drive to explore the environment in ways that reveal its underlying causal structure. But are they really attuned specifically to casual information in this quest for understanding, or do they show equal interest in other types of non-obvious information about the world? To answer this question, we introduced 20 three-year-old children to two puppets who were anxious to tell the child about a set of novel artifacts and animals. One puppet consistently described causal properties of the items while the other puppet consistently described carefully matched non-causal properties of the same items. After a familiarization period in which children learned which type of information to expect from each informant, children were given the opportunity to choose which they wanted to hear describe each of eight pictured test items. On average, children chose to hear from the informant that provided causal descriptions on 72% of the trials. This preference for causal information has important implications for explaining the role of conceptual information in supporting early learning and may suggest means for maximizing interest and motivation in young children. PMID:25762945

  6. Darwin, Veblen and the problem of causality in economics.

    PubMed

    Hodgson, G M

    2001-01-01

    This article discusses some of the ways in which Darwinism has influenced a small minority of economists. It is argued that Darwinism involves a philosophical as well as a theoretical doctrine. Despite claims to the contrary, the uses of analogies to Darwinian natural selection theory are highly limited in economics. Exceptions include Thorstein Veblen, Richard Nelson, and Sidney Winter. At the philosophical level, one of the key features of Darwinism is its notion of detailed understanding in terms of chains of cause and effect. This issue is discussed in the context of the problem of causality in social theory. At least in Darwinian terms, the prevailing causal dualism--of intentional and mechanical causality--in the social sciences is found wanting. Once again, Veblen was the first economist to understand the implications for economics of Darwinism at this philosophical level. For Veblen, it was related to his notion of 'cumulative causation'. The article concludes with a discussion of the problems and potential of this Veblenian position. PMID:12472063

  7. Implications of Einstein-Weyl Causality on Quantum Mechanics

    NASA Astrophysics Data System (ADS)

    Bendaniel, David

    A fundamental physical principle that has consequences for the topology of space-time is the principle of Einstein-Weyl causality. This also has quantum mechanical manifestations. Borchers and Sen have rigorously investigated the mathematical implications of Einstein-Weyl causality and shown the denumerable space-time Q2 would be implied. They were left with important philosophical paradoxes regarding the nature of the physical real line E, e.g., whether E = R, the real line of mathematics. In order to remove these paradoxes an investigation into a constructible foundation is suggested. We have pursued such a program and find it indeed provides a dense, denumerable space-time and, moreover, an interesting connection with quantum mechanics. We first show that this constructible theory contains polynomial functions which are locally homeomorphic with a dense, denumerable metric space R* and are inherently quantized. Eigenfunctions governing fields can then be effectively obtained by computational iteration. Postulating a Lagrangian for fields in a compactified space-time, we get a general description of which the Schrodinger equation is a special case. From these results we can then also show that this denumerable space-time is relational (in the sense that space is not infinitesimally small if and only if it contains a quantized field) and, since Q2 is imbedded in R*2, it directly fulfills the strict topological requirements for Einstein-Weyl causality. Therefore, the theory predicts that E = R*.

  8. Causality, renormalizability and ultra-high energy gravitational scattering

    NASA Astrophysics Data System (ADS)

    Hollowood, Timothy J.; Shore, Graham M.

    2016-05-01

    The amplitude { A }(s,t) for ultra-high energy scattering can be found in the leading eikonal approximation by considering propagation in an Aichelburg–Sexl gravitational shockwave background. Loop corrections in the QFT describing the scattered particles are encoded for energies below the Planck scale in an effective action which in general exhibits causality violation and Shapiro time advances. In this paper, we use Penrose limit techniques to calculate the full energy dependence of the scattering phase shift {{{\\Theta }}}{{scat}}(\\hat{s}), where the single variable \\hat{s}={Gs}/{m}2{b}d-2 contains both the CM energy s and impact parameter b, for a range of scalar QFTs in d dimensions with different renormalizability properties. We evaluate the high-energy limit of {{{\\Theta }}}{{scat}}(\\hat{s}) and show in detail how causality is related to the existence of a well-defined UV completion. Similarities with graviton scattering and the corresponding resolution of causality violation in the effective action by string theory are briefly discussed.

  9. Causal models of trip replanning in TravTek

    SciTech Connect

    Schryver, J.C.

    1998-07-01

    The TravTek operational field test was conducted to evaluate the effectiveness of route planning, route guidance and various navigational aiding modalities for Advanced Traveler Information Systems in ground vehicles. A causal network was constructed in order to achieve a better understanding of the dependencies among variables implicated in the replanning process. Causal inferences were modeled using path analysis techniques. The original Yoked Driver study reported that addition of real-time navigation planning did not increase trip efficiency during initial trip planning. Data mining of the relatively complete database revealed that the incidence of dynamic trip replanning was only 0.51% or 1 out of every 198 trips. Nevertheless, the replanning acceptance rate was 92.8%, suggesting that less conservative criteria might have been acceptable to drivers. Several points can be made based upon the path analysis techniques. Drivers who rejected better route offers were more likely to be male renters; rejected routes were apparently offered at earlier times with a lower predicted time savings and fewer maneuvers. Failure to accept a better route also apparently resulted in fewer wrong-turn deviations. Contrary to expectations, wrong-turn count and time loss appeared as semi-independent hubs in the resultant causal network. Implications of the path analysis are discussed. Proposals for in-vehicle information systems are formulated to increase driver participation as co-planner, and increase the likelihood that trip replanning will positively impact trip efficiency.

  10. The Newtonian approximation in Causal Dynamical Triangulations

    NASA Astrophysics Data System (ADS)

    Getchell, Adam

    2015-04-01

    I review how to derive Newton's law of universal gravitation from the Weyl strut between two Chazy-Curzon particles. I also briefly review Causal Dynamical Triangulations (CDT), a method for evaluating the path integral from canonical quantum gravity using Regge calculus and restrictions of the class of simplicial manifolds evaluated to those with a defined time foliation, thus enforcing a causal structure. I then discuss how to apply this approach to Causal Dynamical Triangulations, in particular modifying the algorithm to keep two simplicial submanifolds with curvature (i.e. mass) a fixed distance from each other, modulo regularized deviations and across all time slices. I then discuss how to determine if CDT produces an equivalent Weyl strut, which can then be used to obtain the Newtonian limit. I wrap up with a brief discussion of computational methods and code development.

  11. Normalizing the causality between time series.

    PubMed

    Liang, X San

    2015-08-01

    Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market. PMID:26382363

  12. Causal Mediation Analyses for Randomized Trials.

    PubMed

    Lynch, Kevin G; Cary, Mark; Gallop, Robert; Ten Have, Thomas R

    2008-01-01

    In the context of randomized intervention trials, we describe causal methods for analyzing how post-randomization factors constitute the process through which randomized baseline interventions act on outcomes. Traditionally, such mediation analyses have been undertaken with great caution, because they assume that the mediating factor is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability). Because the mediating factors are typically not randomized, such analyses are unprotected from unmeasured confounders that may lead to biased inference. We review several causal approaches that attempt to reduce such bias without assuming that the mediating factor is randomized. However, these causal approaches require certain interaction assumptions that may be assessed if there is enough treatment heterogeneity with respect to the mediator. We describe available estimation procedures in the context of several examples from the literature and provide resources for software code. PMID:19484136

  13. The causal meaning of Hamilton's rule.

    PubMed

    Okasha, Samir; Martens, Johannes

    2016-03-01

    Hamilton's original derivation of his rule for the spread of an altruistic gene (rb>c) assumed additivity of costs and benefits. Recently, it has been argued that an exact version of the rule holds under non-additive pay-offs, so long as the cost and benefit terms are suitably defined, as partial regression coefficients. However, critics have questioned both the biological significance and the causal meaning of the resulting rule. This paper examines the causal meaning of the generalized Hamilton's rule in a simple model, by computing the effect of a hypothetical experiment to assess the cost of a social action and comparing it to the partial regression definition. The two do not agree. A possible way of salvaging the causal meaning of Hamilton's rule is explored, by appeal to R. A. Fisher's 'average effect of a gene substitution'. PMID:27069669

  14. Multisensory causal inference in the brain.

    PubMed

    Kayser, Christoph; Shams, Ladan

    2015-02-01

    At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions. PMID:25710476

  15. Normalizing the causality between time series

    NASA Astrophysics Data System (ADS)

    Liang, X. San

    2015-08-01

    Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

  16. Identification of causal genes for complex traits

    PubMed Central

    Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

    2015-01-01

    Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484

  17. The Causal Boundary Of Standard Stationary Spacetimes

    SciTech Connect

    Flores, Jose L.

    2009-05-01

    In this paper we present a description of the causal boundary for the class of standard stationary spacetimes: With (M,g{sub 0}) an arbitrary Riemannian manifold and {omega} a one-form on M, the causal boundary of (V = RxM,g -dt{sup 2}+{omega} x dt+dt x {omega}+g{sub 0}) is given in terms of a Busemann boundary construction on manifolds (M,F{sub {+-}}), with F{sub {+-}} Finsler metrics associated to {omega} and g{sub 0}.

  18. A significant causal association between C-reactive protein levels and schizophrenia

    PubMed Central

    Inoshita, Masatoshi; Numata, Shusuke; Tajima, Atsushi; Kinoshita, Makoto; Umehara, Hidehiro; Nakataki, Masahito; Ikeda, Masashi; Maruyama, Souichiro; Yamamori, Hidenaga; Kanazawa, Tetsufumi; Shimodera, Shinji; Hashimoto, Ryota; Imoto, Issei; Yoneda, Hiroshi; Iwata, Nakao; Ohmori, Tetsuro

    2016-01-01

    Many observational studies have shown elevated blood CRP levels in schizophrenia compared with controls, and one population-based prospective study has reported that elevated plasma CRP levels were associated with late- and very-late-onset schizophrenia. Furthermore, several clinical studies have reported the efficacy of anti-inflammatory drugs on the symptoms in patients with schizophrenia. However, whether elevated CRP levels are causally related to schizophrenia is not still established because of confounding factors and reverse causality. In the present study, we demonstrated that serum CRP levels were significantly higher in patients with schizophrenia than in the controls by conducting a case-control study and a meta-analysis of case-control studies between schizophrenia and serum CRP levels. Furthermore, we provided evidence for a causal association between elevated CRP levels and increased schizophrenia risk by conducting a Mendelian randomization analysis. Our findings suggest that elevated CRP itself may be a causal risk factor for schizophrenia. PMID:27193331

  19. Building a bridge-an archeologist's perspective on the evolution of causal cognition.

    PubMed

    Haidle, Miriam N

    2014-01-01

    The cognitive capacities of fossil humans cannot be studied directly. Taking the evolution of causal cognition as an example this article demonstrates the use of bridging arguments from archeological finds as starting point via identification/classification, behavioral reconstructions, and cognitive interpretations to psychological models. Generally, tool use is linked to some causal understanding/agent construal as the tool broadens the subject's specific capabilities by adding new characters to its action sphere. In human evolution, the distance between the primarily perceived problem and the solution satisfying this need increased markedly: from simple causal relations to effective chaining in secondary/modular tool use, and further to the use of composite tools, complementary tool sets and notional tools. This article describes the evolution of human tool behavior from the perspective of problem-solution-distance and discusses the implications for a linked development of causal cognition. PMID:25566147

  20. Building a bridge—an archeologist's perspective on the evolution of causal cognition

    PubMed Central

    Haidle, Miriam N.

    2014-01-01

    The cognitive capacities of fossil humans cannot be studied directly. Taking the evolution of causal cognition as an example this article demonstrates the use of bridging arguments from archeological finds as starting point via identification/classification, behavioral reconstructions, and cognitive interpretations to psychological models. Generally, tool use is linked to some causal understanding/agent construal as the tool broadens the subject's specific capabilities by adding new characters to its action sphere. In human evolution, the distance between the primarily perceived problem and the solution satisfying this need increased markedly: from simple causal relations to effective chaining in secondary/modular tool use, and further to the use of composite tools, complementary tool sets and notional tools. This article describes the evolution of human tool behavior from the perspective of problem-solution-distance and discusses the implications for a linked development of causal cognition. PMID:25566147

  1. Validation of Candidate Causal Genes for Abdominal Obesity Which Affect Shared Metabolic Pathways and Networks

    PubMed Central

    Yang, Xia; Deignan, Joshua L.; Qi, Hongxiu; Zhu, Jun; Qian, Su; Zhong, Judy; Torosyan, Gevork; Majid, Sana; Falkard, Brie; Kleinhanz, Robert R.; Karlsson, Jenny; Castellani, Lawrence W.; Mumick, Sheena; Wang, Kai; Xie, Tao; Coon, Michael; Zhang, Chunsheng; Estrada-Smith, Daria; Farber, Charles R.; Wang, Susanna S.; Van Nas, Atila; Ghazalpour, Anatole; Zhang, Bin; MacNeil, Douglas J.; Lamb, John R.; Dipple, Katrina M.; Reitman, Marc L.; Mehrabian, Margarete; Lum, Pek Y.; Schadt, Eric E.; Lusis, Aldons J.

    2010-01-01

    A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes and identification of involved pathways and networks. PMID:19270708

  2. A significant causal association between C-reactive protein levels and schizophrenia.

    PubMed

    Inoshita, Masatoshi; Numata, Shusuke; Tajima, Atsushi; Kinoshita, Makoto; Umehara, Hidehiro; Nakataki, Masahito; Ikeda, Masashi; Maruyama, Souichiro; Yamamori, Hidenaga; Kanazawa, Tetsufumi; Shimodera, Shinji; Hashimoto, Ryota; Imoto, Issei; Yoneda, Hiroshi; Iwata, Nakao; Ohmori, Tetsuro

    2016-01-01

    Many observational studies have shown elevated blood CRP levels in schizophrenia compared with controls, and one population-based prospective study has reported that elevated plasma CRP levels were associated with late- and very-late-onset schizophrenia. Furthermore, several clinical studies have reported the efficacy of anti-inflammatory drugs on the symptoms in patients with schizophrenia. However, whether elevated CRP levels are causally related to schizophrenia is not still established because of confounding factors and reverse causality. In the present study, we demonstrated that serum CRP levels were significantly higher in patients with schizophrenia than in the controls by conducting a case-control study and a meta-analysis of case-control studies between schizophrenia and serum CRP levels. Furthermore, we provided evidence for a causal association between elevated CRP levels and increased schizophrenia risk by conducting a Mendelian randomization analysis. Our findings suggest that elevated CRP itself may be a causal risk factor for schizophrenia. PMID:27193331

  3. INTERNAL VS EXTERNAL SUBSTORM TRIGGERS: TRANSFER ENTROPY AS A MEASURE OF CAUSALITY

    NASA Astrophysics Data System (ADS)

    Snider, R.; Johnson, J.; Wing, S.; Echim, M.

    2009-12-01

    We examine the expanded substorm dataset compiled by Frey [J. Geophys. Res., 109, A10304, 2004] to evaluate the question of internal vs external triggering of substorms [see Hsu and McPherron, J. Geophys. Res., 107, 1398, 2002; Morley and Freeman, Geophys. Res. Lett., 34, L08104, 2006] using transfer entropy as a measure of causality. Transfer entropy is particularly useful to identify causal relationships in data sets because: (a) it is highly directional, (b) it includes higher order, nonlinear correlations, and (c) it can distinguish between variables that are correlated because of a common driver and variables that are causally correlated. We discuss how these properties of transfer entropy are useful for analysis of space data sets, and we examine the extent to which solar wind fluctuations are causally related to substorm onset.

  4. [Use of causal diagrams in Epidemiology: application to a situation with confounding].

    PubMed

    Cortes, Taísa Rodrigues; Faerstein, Eduardo; Struchiner, Claudio José

    2016-08-01

    Epidemiological research still rarely uses causal diagrams, despite growing recognition of their explanatory potential. One possible reason is that many research programs involve themes in which there is a certain degree of uncertainty as to mechanisms in the processes that generate the data. In this study, the relationship between occupational stress and obesity is used as an example of the application of causal diagrams to questions related to confounding. The article presents the selection stages for variables in statistical adjustment and the derivation of a causal diagram's statistical implications. The main advantage of causal diagrams is that they explicitly reveal the respective model's underlying hypotheses, allowing critical analysis of the implications and thereby facilitating identification of sources of bias and uncertainty in the epidemiological study's results. PMID:27509550

  5. Just do it? Investigating the gap between prediction and action in toddlers’ causal inferences

    PubMed Central

    Bonawitz, Elizabeth Baraff; Ferranti, Darlene; Saxe, Rebecca; Gopnik, Alison; Meltzoff, Andrew N.; Woodward, James; Schulz, Laura E.

    2011-01-01

    Adults’ causal representations integrate information about predictive relations and the possibility of effective intervention; if one event reliably predicts another, adults can represent the possibility that acting to bring about the first event might generate the second. Here we show that although toddlers (mean age: 24 months) readily learn predictive relationships between physically connected events, they do not spontaneously initiate one event to try to generate the second (although older children, mean age: 47 months, do; Experiments 1 and 2). Toddlers succeed only when the events are initiated by a dispositional agent (Experiment 3), when the events involve direct contact between objects (Experiment 4), or when the events are described using causal language (Experiment 5). This suggests that causal language may help children extend their initial causal representations beyond agent-initiated and direct contact events. PMID:20097329

  6. Granger causality analysis with nonuniform sampling and its application to pulse-coupled nonlinear dynamics

    NASA Astrophysics Data System (ADS)

    Zhang, Yaoyu; Xiao, Yanyang; Zhou, Douglas; Cai, David

    2016-04-01

    The Granger causality (GC) analysis is an effective approach to infer causal relations for time series. However, for data obtained by uniform sampling (i.e., with an equal sampling time interval), it is known that GC can yield unreliable causal inference due to aliasing if the sampling rate is not sufficiently high. To solve this unreliability issue, we consider the nonuniform sampling scheme as it can mitigate against aliasing. By developing an unbiased estimation of power spectral density of nonuniformly sampled time series, we establish a framework of spectrum-based nonparametric GC analysis. Applying this framework to a general class of pulse-coupled nonlinear networks and utilizing some particular spectral structure possessed by these nonlinear network data, we demonstrate that, for such nonlinear networks with nonuniformly sampled data, reliable GC inference can be achieved at a low nonuniform mean sampling rate at which the traditional uniform sampling GC may lead to spurious causal inference.

  7. Causal Inferences with Group Based Trajectory Models

    ERIC Educational Resources Information Center

    Haviland, Amelia M.; Nagin, Daniel S.

    2005-01-01

    A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This paper lays out and applies a method for using observational longitudinal data to make more confident causal inferences about the…

  8. Dimensional Reduction in Causal Set Gravity

    NASA Astrophysics Data System (ADS)

    Carlip, Steven

    2016-03-01

    Several different approaches to quantum gravity indicate that the effective dimension of spacetime falls to approximately two at very short distances. I provide evidence for similar behavior in the causal set approach to quantum gravity. Supported in part by Department of Energy Grant DE-FG02-91ER40674.

  9. Escaping Myopia: Teaching Students about Historical Causality

    ERIC Educational Resources Information Center

    Waring, Scott M.

    2010-01-01

    There are so many aspects to teaching history that are vital to creating well-rounded historical thinkers, but one of the most fundamental and most overlooked elements is the idea of causality. Far too many students do not understand the idea of causation, that there are multiple reasons for why historical events occurred and transpired in the way…

  10. The metagenomic approach and causality in virology

    PubMed Central

    Castrignano, Silvana Beres; Nagasse-Sugahara, Teresa Keico

    2015-01-01

    Nowadays, the metagenomic approach has been a very important tool in the discovery of new viruses in environmental and biological samples. Here we discuss how these discoveries may help to elucidate the etiology of diseases and the criteria necessary to establish a causal association between a virus and a disease. PMID:25902566

  11. Exploring Causal Models of Educational Achievement.

    ERIC Educational Resources Information Center

    Parkerson, Jo Ann; And Others

    1984-01-01

    This article evaluates five causal model of educational productivity applied to learning science in a sample of 882 fifth through eighth graders. Each model explores the relationship between achievement and a combination of eight constructs: home environment, peer group, media, ability, social environment, time on task, motivation, and…

  12. Inductive Reasoning about Causally Transmitted Properties

    ERIC Educational Resources Information Center

    Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D.; Tenenbaum, Joshua B.

    2008-01-01

    Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates'…

  13. Causality and the stability of parallel flow

    NASA Astrophysics Data System (ADS)

    Chimonas, George

    1991-11-01

    The linearized theory of the stability of parallel flow is formulated in terms of causality theory. In this method the properties of the Fourier spectrum—the disturbances with real frequency ω—provide the stability criteria for a system. In particular, if the Fourier spectrum provides a complete cause-and-effect formulation, the flow is assuredly stable. This single restriction leads to the critical-level theorems for parallel flows in both stably and unstably stratified fluids, Howard's semicircle theorem, the Miles-Howard Richardson-number criterion, an extended semicircle theorem for unstable flows, and several other results concerning instabilities in fluids. The causal approach supersedes group-velocity concepts, and resolves the problems of defining upward- and downward-propagating signals in a rapidly varying medium. It also associates a causal behavior to scattering from a discontinuity or an interface. Causality is examined by subdividing the continuous fluid into a set of homogeneous intervals within which propagation and interfacial scattering can be explicitly computed. As the intervals are reduced toward infinitesimal size the solution for the continuous fluid is obtained.

  14. Simplicity and Probability in Causal Explanation

    ERIC Educational Resources Information Center

    Lombrozo, Tania

    2007-01-01

    What makes some explanations better than others? This paper explores the roles of simplicity and probability in evaluating competing causal explanations. Four experiments investigate the hypothesis that simpler explanations are judged both better and more likely to be true. In all experiments, simplicity is quantified as the number of causes…

  15. Introducing Mechanics by Tapping Core Causal Knowledge

    ERIC Educational Resources Information Center

    Klaassen, Kees; Westra, Axel; Emmett, Katrina; Eijkelhof, Harrie; Lijnse, Piet

    2008-01-01

    This article concerns an outline of an introductory mechanics course. It is based on the argument that various uses of the concept of force (e.g. from Kepler, Newton and everyday life) share an explanatory strategy based on core causal knowledge. The strategy consists of (a) the idea that a force causes a deviation from how an object would move of…

  16. Causal and Teleological Explanations in Biology

    ERIC Educational Resources Information Center

    Yip, Cheng-Wai

    2009-01-01

    A causal explanation in biology focuses on the mechanism by which a biological process is brought about, whereas a teleological explanation considers the end result, in the context of the survival of the organism, as a reason for certain biological processes or structures. There is a tendency among students to offer a teleological explanation…

  17. Causality and Teleology in High School Biology.

    ERIC Educational Resources Information Center

    Tamir, Pinchas

    1985-01-01

    Ability to distinguish between causal (cause-effect) and teleological (means-ends) explanations was measured in 1905 twelfth-grade biology students and found to be dependent on student knowledge. Although the inability to make these distinctions contributes to misconceptions in biology, appropriate instruction can easily remedy the problem. Sample…

  18. Comments: Causal Interpretations of Mediation Effects

    ERIC Educational Resources Information Center

    Jo, Booil; Stuart, Elizabeth A.

    2012-01-01

    The authors thank Dr. Lindsay Page for providing a nice illustration of the use of the principal stratification framework to define causal effects, and a Bayesian model for effect estimation. They hope that her well-written article will help expose education researchers to these concepts and methods, and move the field of mediation analysis in…

  19. Constructing Causal Diagrams to Learn Deliberation

    ERIC Educational Resources Information Center

    Easterday, Matthew W.; Aleven, Vincent; Scheines, Richard; Carver, Sharon M.

    2009-01-01

    Policy problems like "What should we do about global warming?" are ill-defined in large part because we do not agree on a system to represent them the way we agree Algebra problems should be represented by equations. As a first step toward building a policy deliberation tutor, we investigated: (a) whether causal diagrams help students learn to…

  20. Connecting Scientific Reasoning and Causal Inference

    ERIC Educational Resources Information Center

    Kuhn, Deanna; Dean, David, Jr.

    2004-01-01

    Literature on multivariable causal inference (MCI) and literature on scientific reasoning (SR) have proceeded almost entirely independently, although they in large part address the same phenomena. An effort is made to bring these paradigms into close enough alignment with one another to compare implications of the two lines of work and examine how…

  1. THE CHILD'S CONCEPTION OF PHYSICAL CAUSALITY.

    ERIC Educational Resources Information Center

    PIAGET, JEAN

    THE CHILD'S CONCEPTION OF PHYSICAL CAUSALITY WAS INVESTIGATED. THREE METHODS OF INVESTIGATION WERE USED. THE FIRST METHOD WAS PURELY VERBAL, AND CONSISTED OF A SERIES OF QUESTIONS DIRECTED TO CHILDREN, REGARDING SOME NATURAL PHENOMENON. THE SECOND METHOD INVOLVED A HALF-VERBAL, HALF-PRACTICAL APPROACH, WHEREIN A SPECIFIC REFERENCE TO NATURAL…

  2. Time and Order Effects on Causal Learning

    ERIC Educational Resources Information Center

    Alvarado, Angelica; Jara, Elvia; Vila, Javier; Rosas, Juan M.

    2006-01-01

    Five experiments were conducted to explore trial order and retention interval effects upon causal predictive judgments. Experiment 1 found that participants show a strong effect of trial order when a stimulus was sequentially paired with two different outcomes compared to a condition where both outcomes were presented intermixed. Experiment 2…

  3. Linear Response Laws and Causality in Electrodynamics

    ERIC Educational Resources Information Center

    Yuffa, Alex J.; Scales, John A.

    2012-01-01

    Linear response laws and causality (the effect cannot precede the cause) are of fundamental importance in physics. In the context of classical electrodynamics, students often have a difficult time grasping these concepts because the physics is obscured by the intermingling of the time and frequency domains. In this paper, we analyse the linear…

  4. Interpretational Confounding or Confounded Interpretations of Causal Indicators?

    PubMed Central

    Bainter, Sierra A.; Bollen, Kenneth A.

    2014-01-01

    In measurement theory causal indicators are controversial and little-understood. Methodological disagreement concerning causal indicators has centered on the question of whether causal indicators are inherently sensitive to interpretational confounding, which occurs when the empirical meaning of a latent construct departs from the meaning intended by a researcher. This article questions the validity of evidence used to claim that causal indicators are inherently susceptible to interpretational confounding. Further, a simulation study demonstrates that causal indicator coefficients are stable across correctly-specified models. Determining the suitability of causal indicators has implications for the way we conceptualize measurement and build and evaluate measurement models. PMID:25530730

  5. Elaborations for the Validation of Causal Bridging Inferences in Text Comprehension.

    PubMed

    Morishima, Yasunori

    2016-08-01

    The validation model of causal bridging inferences proposed by Singer and colleagues (e.g., Singer in Can J Exp Psychol, 47(2):340-359, 1993) claims that before a causal bridging inference is accepted, it must be validated by existing knowledge. For example, to understand "Dorothy took the aspirins. Her pain went away," one first computes a mediating idea RELIEVE [ASPIRIN, PAIN]. Then, the truth of it is validated on the basis of existing knowledge. The present study examined the hypothesis that a causal inference would be drawn and validated even when validating knowledge is not familiar or available because elaborations are made to retrieve or construct such knowledge. Experiment 1 showed that people tend to judge naturalness of a text based on causal relations and that causality was indeed recognized in those texts in which the antecedent sentence and the consequence sentence are not linked by familiar knowledge. Experiment 2, which measured sentence reading times, showed that while sentence processing times were longer for such texts than texts involving familiar knowledge, there was no difference between these texts in reading the subsequent sentence describing the validating idea. These results provided evidence supporting elaboration as well as validation of causal bridging inferences. PMID:26210351

  6. Identification of Dominant Excitation Patterns and Sources of Atrial Fibrillation by Causality Analysis.

    PubMed

    Rodrigo, Miguel; Climent, Andreu M; Liberos, Alejandro; Calvo, David; Fernández-Avilés, Francisco; Berenfeld, Omer; Atienza, Felipe; Guillem, Maria S

    2016-08-01

    Burden of atrial fibrillation (AF) can be reduced by ablation of sources of electrical impulses driving AF but driver identification is still challenging. This study presents a new methodology based on causality analysis that allows identifying the hierarchically dominant areas driving AF. Identification of dominant propagation patterns was achieved by computing causal relations between intracardiac multi-electrode catheter recordings of four paroxysmal AF patients during sinus rhythm, pacing and AF. In addition, realistic mathematical models of the atria during AF were used to validate the methodology both in the presence and absence of dominant frequency (DF) gradients. During electrical pacing, sources of propagation patterns detected by causality analysis were consistent with the location of the stimulating catheter. During AF, propagation patterns presented temporal variability, but a dominant direction accounted for significantly more propagations than other directions (49 ± 15% vs. 14 ± 13% or less, p < 0.01). Both in patients with a DF gradient and in mathematical models, causal maps allowed the identification of sites responsible for maintenance of AF. Causal maps allowed the identification of atrial dominant sites. In particular, causality analysis resulted in stable dominant cause-effect propagation directions during AF and could serve as a guide for performing ablation procedures in AF patients. PMID:26850022

  7. Estimating Granger causality after stimulus onset: A cautionary note

    PubMed Central

    Wang, Xue; Chen, Yonghong; Ding, Mingzhou

    2008-01-01

    How the brain processes sensory input to produce goal-oriented behavior is not well-understood. Advanced data acquisition technology in conjunction with novel statistical methods holds the key to future progress in this area. Recent studies have applied Granger causality to multivariate population recordings such as local field potential (LFP) or electroencephalography (EEG) in event-related paradigms. The aim is to reveal the detailed time course of stimulus-elicited information transaction among various sensory and motor cortices. Presently, interdependency measures like coherence and Granger causality are calculated on ongoing brain activity obtained by removing the average event-related potential (AERP) from each trial. In this paper we point out the pitfalls of this approach in light of the inevitable occurrence of trial-to-trial variability of event-related potentials in both amplitudes and latencies. Numerical simulations and experimental examples are used to illustrate the ideas. Special emphasis is placed on the important role played by single trial analysis of event-related potentials in experimentally establishing the main conclusion. PMID:18455441

  8. A new causal interpretation of EPR-B experiment

    NASA Astrophysics Data System (ADS)

    Gondran, Michel; Gondran, Alexandre

    2012-12-01

    In this paper we study a two-step version of EPR-B experiment, the Bohm version of the Einstein-Podolsky-Rosen experiment. Its theoretical resolution in space and time enables us to refute the classic "impossibility" to decompose a pair of entangled atoms into two distinct states, one for each atom. We propose a new causal interpretation of the EPR-B experiment where each atom has a position and a spin while the singlet wave function verifies the two-body Pauli equation. In conclusion we suggest a physical explanation of non-local influences, compatible with Einstein's point of view on relativity.

  9. Causal simulation and sensor planning in predictive monitoring

    NASA Technical Reports Server (NTRS)

    Doyle, Richard J.

    1989-01-01

    Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.

  10. Implications of the causality principle for ultra chiral metamaterials

    PubMed Central

    Gorkunov, Maxim V.; Dmitrienko, Vladimir E.; Ezhov, Alexander A.; Artemov, Vladimir V.; Rogov, Oleg Y.

    2015-01-01

    Chiral metamaterials – artificial subwavelength structures with broken mirror symmetry – demonstrate outstanding degree of optical chirality that exhibits sophisticated spectral behavior and can eventually reach extreme values. Based on the fundamental causality principle we show how one can unambiguously relate the metamaterial circular dichroism and optical activity by the generalized Kramers-Kronig relations. Contrary to the conventional relations, the generalized ones provide a unique opportunity of extracting information on material-dependent zeroes of transmission coefficient in the upper half plane of complex frequency. We illustrate the merit of the formulated relations by applying them to the observed ultra chiral optical transmission spectra of subwavelength arrays of chiral holes in silver films. Apart from the possibility of precise verification of experimental data, the relations enable resolving complex eigenfrequencies of metamaterial intrinsic modes and resonances. PMID:25787007

  11. From Granger causality to long-term causality: Application to climatic data

    NASA Astrophysics Data System (ADS)

    Smirnov, Dmitry A.; Mokhov, Igor I.

    2009-07-01

    Quantitative characterization of interaction between processes from time series is often required in different fields of natural science including geophysics and biophysics. Typically, one estimates “short-term” influences, e.g., the widely used Granger causality is defined via one-step-ahead predictions. Such an approach does not reveal how strongly the “long-term” behavior of one process under study is affected by the others. To overcome this problem, we introduce the concept of long-term causality, which extends the concept of Granger causality. The long-term causality is estimated from data via empirical modeling and analysis of model dynamics under different conditions. Apart from mathematical examples, we apply both approaches to find out how strongly the global surface temperature (GST) is affected by variations in carbon dioxide atmospheric content, solar activity, and volcanic activity during the last 150 years. Influences of all the three factors on GST are detected with the Granger causality. However, the long-term causality shows that the rise in GST during the last decades can be explained only if the anthropogenic factor (CO2) is taken into account in a model.

  12. The influence of causal connections between symptoms on the diagnosis of mental disorders: evidence from online and offline measures.

    PubMed

    Flores, Amanda; Cobos, Pedro L; López, Francisco J; Godoy, Antonio; González-Martín, Estrella

    2014-09-01

    An experiment conducted with students and experienced clinicians demonstrated very fast and online causal reasoning in the diagnosis of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) mental disorders. The experiment also demonstrated that clinicians' causal reasoning is triggered by information that is directly related to the causal structure that explains the symptoms, such as their temporal sequence. The use of causal theories was measured through explicit, verbal diagnostic judgments and through the online registration of participants' reading times of clinical reports. To detect both online and offline causal reasoning, the consistency of clinical reports was manipulated. This manipulation was made by varying the temporal order in which different symptoms developed in hypothetical clients, and by providing explicit information about causal connections between symptoms. The temporal order of symptoms affected the clinicians' but not the students' reading times. However, offline diagnostic judgments in both groups were influenced by the consistency manipulation. Overall, our results suggest that clinicians engage in fast and online causal reasoning processes when dealing with diagnostic information concerning mental disorders, and that both clinicians and students engage in causal reasoning in diagnostic judgment tasks. PMID:25068482

  13. Exploratory Causal Analysis in Bivariate Time Series Data

    NASA Astrophysics Data System (ADS)

    McCracken, James M.

    Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

  14. Vitamin D and extra-skeletal health: causality or consequence

    PubMed Central

    Al Nozha, Omar M.

    2016-01-01

    Vitamin D deficiency /insufficiency is widely recognized as a global health problem that is likely to be involved in pathogenesis or progression of many acute and chronic health disorders. Its relation to skeletal health has been clearly demonstrated and thoroughly examined. This review aims to highlight the continuous debate about the relation between vitamin D and extra-skeletal health and whether it is a causality or just an association. Overall, the available evidence does not meet the criteria for establishing cause-and-effect relationships because of the limitations of observational studies to corroborate the causality due to many potential confounders. Moreover, the causal relationship couldn’t be established in randomized studies or in many meta-analyses. This may reflect the fact that vitamin D level reduction is just a biomarker of ill health. The inflammatory processes involved in the disease occurrence and the functional limitations of the diseases would have a role in reducing serum 25-hydroxy vitamin D “25 (OH) D” level, which would explain why low vitamin D is reported in a wide range of disorders. This may underscore the possibility of harm instead of benefit of vitamin D supplementation when its exact role is not fully established, thus many guidelines and interest groups are still hesitant toward recommending replacement in extra-skeletal disease. Future directions entails the need for a large well-designed randomized control trials (RCTs) to resolve the active debate on the benefits of vitamin D replacement for extra-skeletal disease, and not only that, future studies should establish specific, clinically relevant effects of vitamin D repletion, provide cut-values for optimal serum levels of 25 (OH) D, and appropriate doses for non-skeletal health benefits. PMID:27610068

  15. Vitamin D and extra-skeletal health: causality or consequence.

    PubMed

    Al Nozha, Omar M

    2016-07-01

    Vitamin D deficiency /insufficiency is widely recognized as a global health problem that is likely to be involved in pathogenesis or progression of many acute and chronic health disorders. Its relation to skeletal health has been clearly demonstrated and thoroughly examined. This review aims to highlight the continuous debate about the relation between vitamin D and extra-skeletal health and whether it is a causality or just an association. Overall, the available evidence does not meet the criteria for establishing cause-and-effect relationships because of the limitations of observational studies to corroborate the causality due to many potential confounders. Moreover, the causal relationship couldn't be established in randomized studies or in many meta-analyses. This may reflect the fact that vitamin D level reduction is just a biomarker of ill health. The inflammatory processes involved in the disease occurrence and the functional limitations of the diseases would have a role in reducing serum 25-hydroxy vitamin D "25 (OH) D" level, which would explain why low vitamin D is reported in a wide range of disorders. This may underscore the possibility of harm instead of benefit of vitamin D supplementation when its exact role is not fully established, thus many guidelines and interest groups are still hesitant toward recommending replacement in extra-skeletal disease. Future directions entails the need for a large well-designed randomized control trials (RCTs) to resolve the active debate on the benefits of vitamin D replacement for extra-skeletal disease, and not only that, future studies should establish specific, clinically relevant effects of vitamin D repletion, provide cut-values for optimal serum levels of 25 (OH) D, and appropriate doses for non-skeletal health benefits. PMID:27610068

  16. Perceived Causalities of Physical Events Are Influenced by Social Cues

    ERIC Educational Resources Information Center

    Zhou, Jifan; Huang, Xiang; Jin, Xinyi; Liang, Junying; Shui, Rende; Shen, Mowei

    2012-01-01

    In simple mechanical events, we can directly perceive causal interactions of the physical objects. Physical cues (especially spatiotemporal features of the display) are found to associate with causal perception. Here, we demonstrate that cues of a completely different domain--"social cues"--also impact the causal perception of "physical" events:…

  17. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

    ERIC Educational Resources Information Center

    Lu, Hongjing; Rojas, Randall R.; Beckers, Tom; Yuille, Alan L.

    2016-01-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about…

  18. Plus or Minus Causal Conjunctions: An Aid to Reading Comprehension.

    ERIC Educational Resources Information Center

    Williams, Huw

    1984-01-01

    Causal conjunctions that form a grammatical bridge between simple and complex sentences can be either plus or minus causal conjunctions. The category of plus causal conjunctions includes a "because" group (since, as, because of, owing to, due to, as a result of, as a consequence of) and a "so" group (therefore, hence, consequently, accordingly, as…

  19. Causal and Semantic Relatedness in Discourse Understanding and Representation

    ERIC Educational Resources Information Center

    Wolfe, Michael B. W.; Magliano, Joseph P.; Larsen, Benjamin

    2005-01-01

    Processing time and memory for sentences were examined as a function of the degree of semantic and causal relatedness between sentences in short narratives. In Experiments 1-2B, semantic and causal relatedness between sentence pairs was independently manipulated. Causal relatedness was assessed through pretesting and semantic relatedness was…

  20. Mind and Meaning: Piaget and Vygotsky on Causal Explanation.

    ERIC Educational Resources Information Center

    Beilin, Harry

    1996-01-01

    Piaget's theory has been characterized as descriptive and not explanatory, not qualifying as causal explanation. Piaget was consistent in showing how his theory was both explanatory and causal. Vygotsky also endorsed causal-genetic explanation but, on the basis of knowledge of only Piaget's earliest works, he claimed that Piaget's theory was not…

  1. Functional neuroimaging can support causal claims about brain function

    PubMed Central

    Weber, Matthew J.; Thompson-Schill, Sharon L.

    2013-01-01

    Cognitive neuroscientists habitually deny that functional neuroimaging can furnish causal information about the relationship between brain events and behavior. However, imaging studies do provide causal information about those relationships—though not causal certainty. Although popular portrayals of functional neuroimaging tend to attribute too much inferential power to the technique, we should restrain ourselves from ascribing it too little. PMID:20201629

  2. Interpretational Confounding or Confounded Interpretations of Causal Indicators?

    ERIC Educational Resources Information Center

    Bainter, Sierra A.; Bollen, Kenneth A.

    2014-01-01

    In measurement theory, causal indicators are controversial and little understood. Methodological disagreement concerning causal indicators has centered on the question of whether causal indicators are inherently sensitive to interpretational confounding, which occurs when the empirical meaning of a latent construct departs from the meaning…

  3. A Quantitative Causal Model Theory of Conditional Reasoning

    ERIC Educational Resources Information Center

    Fernbach, Philip M.; Erb, Christopher D.

    2013-01-01

    The authors propose and test a causal model theory of reasoning about conditional arguments with causal content. According to the theory, the acceptability of modus ponens (MP) and affirming the consequent (AC) reflect the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Acceptability…

  4. CAUSAL ANALYSIS AND PROBABILITY DATA: EXAMPLES FOR IMPAIRED AQUATIC CONDITION

    EPA Science Inventory

    Causal analysis is plausible reasoning applied to diagnosing observed effect(s), for example, diagnosing

    cause of biological impairment in a stream. Sir Bradford Hill basically defined the application of causal

    analysis when he enumerated the elements of causality f...

  5. Detecting Causality by Combined Use of Multiple Methods: Climate and Brain Examples

    PubMed Central

    Hirata, Yoshito; Amigó, José M.; Matsuzaka, Yoshiya; Yokota, Ryo; Mushiake, Hajime; Aihara, Kazuyuki

    2016-01-01

    Identifying causal relations from time series is the first step to understanding the behavior of complex systems. Although many methods have been proposed, few papers have applied multiple methods together to detect causal relations based on time series generated from coupled nonlinear systems with some unobserved parts. Here we propose the combined use of three methods and a majority vote to infer causality under such circumstances. Two of these methods are proposed here for the first time, and all of the three methods can be applied even if the underlying dynamics is nonlinear and there are hidden common causes. We test our methods with coupled logistic maps, coupled Rössler models, and coupled Lorenz models. In addition, we show from ice core data how the causal relations among the temperature, the CH4 level, and the CO2 level in the atmosphere changed in the last 800,000 years, a conclusion also supported by irregularly sampled data analysis. Moreover, these methods show how three regions of the brain interact with each other during the visually cued, two-choice arm reaching task. Especially, we demonstrate that this is due to bottom up influences at the beginning of the task, while there exist mutual influences between the posterior medial prefrontal cortex and the presupplementary motor area. Based on our results, we conclude that identifying causality with an appropriate ensemble of multiple methods ensures the validity of the obtained results more firmly. PMID:27380515

  6. Causality Is Inconsistent With Quantum Field Theory

    SciTech Connect

    Wolf, Fred Alan

    2011-11-29

    Causality in quantum field theory means the vanishing of commutators for spacelike separated fields (VCSSF). I will show that VCSSF is not tenable. For VCSSF to be tenable, and therefore, to have both retarded and advanced propagators vanish in the elsewhere, a superposition of negative energy antiparticle and positive energy particle propagators, traveling forward in time, and a superposition of negative energy particle and positive energy antiparticle propagators, traveling backward in time, are required. Hence VCSSF predicts non-vanishing probabilities for both negative energy particles in the forward-through-time direction and positive energy antiparticles in the backwards-through-time direction. Therefore, since VCSSF is unrealizable in a stable universe, tachyonic propagation must occur in denial of causality.

  7. Localizing epileptic seizure onsets with Granger causality

    NASA Astrophysics Data System (ADS)

    Adhikari, Bhim M.; Epstein, Charles M.; Dhamala, Mukesh

    2013-09-01

    Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful surgery, which usually depends on the information obtained from intracranial electroencephalography (IEEG) recordings. The visual criteria and univariate methods of analyzing IEEG recordings have not always produced clarity on the SOZs for resection and ultimate seizure freedom for patients. Here, to contribute to improving the localization of the SOZs and to understanding the mechanism of seizure propagation over the brain, we applied spectral interdependency methods to IEEG time series recorded from patients during seizures. We found that the high-frequency (>80 Hz) Granger causality (GC) occurs before the onset of any visible ictal activity and causal relationships involve the recording electrodes where clinically identifiable seizures later develop. These results suggest that high-frequency oscillatory network activities precede and underlie epileptic seizures, and that GC spectral measures derived from IEEG can assist in precise delineation of seizure onset times and SOZs.

  8. The Causal Effects of Father Absence.

    PubMed

    McLanahan, Sara; Tach, Laura; Schneider, Daniel

    2013-07-01

    The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural experiments, and propensity score matching models. Our assessment is that studies using more rigorous designs continue to find negative effects of father absence on offspring well-being, although the magnitude of these effects is smaller than what is found using traditional cross-sectional designs. The evidence is strongest and most consistent for outcomes such as high school graduation, children's social-emotional adjustment, and adult mental health. PMID:24489431

  9. The Causal Effects of Father Absence

    PubMed Central

    McLanahan, Sara; Tach, Laura; Schneider, Daniel

    2014-01-01

    The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural experiments, and propensity score matching models. Our assessment is that studies using more rigorous designs continue to find negative effects of father absence on offspring well-being, although the magnitude of these effects is smaller than what is found using traditional cross-sectional designs. The evidence is strongest and most consistent for outcomes such as high school graduation, children’s social-emotional adjustment, and adult mental health. PMID:24489431

  10. Loop anomalies in the causal approach

    NASA Astrophysics Data System (ADS)

    Grigore, Dan-Radu

    2015-01-01

    We consider gauge models in the causal approach and study one-loop contributions to the chronological products and the anomalies they produce. We prove that in order greater than 4 there are no one-loop anomalies. Next we analyze one-loop anomalies in the second- and third-order of the perturbation theory. We prove that the even parity contributions (with respect to parity) do not produce anomalies; for the odd parity contributions we reobtain the well-known result.

  11. Causality and the effective range expansion

    SciTech Connect

    Hammer, H.-W.; Lee, Dean

    2010-10-15

    We derive the generalization of Wigner's causality bounds and Bethe's integral formula for the effective range parameter to arbitrary dimension and arbitrary angular momentum. We also discuss the impact of these constraints on the separation of low- and high-momentum scales and universality in low-energy scattering. Some of our results were summarized earlier in a letter publication. In this work, we present full derivations and several detailed examples.

  12. A causal dispositional account of fitness.

    PubMed

    Triviño, Vanessa; Nuño de la Rosa, Laura

    2016-09-01

    The notion of fitness is usually equated to reproductive success. However, this actualist approach presents some difficulties, mainly the explanatory circularity problem, which have lead philosophers of biology to offer alternative definitions in which fitness and reproductive success are distinguished. In this paper, we argue  that none of these alternatives is satisfactory and, inspired by Mumford and Anjum's dispositional theory of causation, we offer a definition of fitness as a causal dispositional property. We argue that, under this framework, the distinctiveness that biologists usually attribute to fitness-namely, the fact that fitness is something different from both the physical traits of an organism and the number of offspring it leaves-can be explained, and the main problems associated with the concept of fitness can be solved. Firstly, we introduce Mumford and Anjum's dispositional theory of causation and present our definition of fitness as a causal disposition. We explain in detail each of the elements involved in our definition, namely: the relationship between fitness and the functional dispositions that compose it, the emergent character of fitness, and the context-sensitivity of fitness. Finally, we explain how fitness and realized fitness, as well as expected and realized fitness are distinguished in our approach to fitness as a causal disposition. PMID:27338570

  13. Causal tapestries for psychology and physics.

    PubMed

    Sulis, William H

    2012-04-01

    Archetypal dynamics is a formal approach to the modeling of information flow in complex systems used to study emergence. It is grounded in the Fundamental Triad of realisation (system), interpretation (archetype) and representation (formal model). Tapestries play a fundamental role in the framework of archetypal dynamics as a formal representational system. They represent information flow by means of multi layered, recursive, interlinked graphical structures that express both geometry (form or sign) and logic (semantics). This paper presents a detailed mathematical description of a specific tapestry model, the causal tapestry, selected for use in describing behaving systems such as appear in psychology and physics from the standpoint of Process Theory. Causal tapestries express an explicit Lorentz invariant transient now generated by means of a reality game. Observables are represented by tapestry informons while subjective or hidden components (for example intellectual and emotional processes) are incorporated into the reality game that determines the tapestry dynamics. As a specific example, we formulate a random graphical dynamical system using causal tapestries. PMID:22452929

  14. Note on gauge invariance and causal propagation

    NASA Astrophysics Data System (ADS)

    Henneaux, Marc; Rahman, Rakibur

    2013-09-01

    Interactions of gauge-invariant systems are severely constrained by several consistency requirements. One is the preservation of the number of gauge symmetries, another is causal propagation. For lower-spin fields, the emphasis is usually put on gauge invariance that happens to be very selective by itself. We demonstrate with an explicit example, however, that gauge invariance, albeit indispensable for constructing interactions, may not suffice as a consistency condition. The chosen example that exhibits this feature is the theory of a massless spin-3/2 field coupled to electromagnetism. We show that this system admits an electromagnetic background in which the spin-3/2 gauge field may move faster than light. Requiring causal propagation rules out otherwise allowed gauge-invariant couplings. This emphasizes the importance of causality analysis as an independent test for a system of interacting gauge fields. We comment on the implications of allowing new degrees of freedom and nonlocality in a theory, on higher-derivative gravity and Vasiliev’s higher-spin theories.

  15. Cohomology Methods in Causal Perturbation Theory

    NASA Astrophysics Data System (ADS)

    Grigore, D. R.

    2010-01-01

    Various problems in perturbation theory of (quantum) gauge models can be rephrased in the language of cohomology theory. This was already noticed in the functional formulation of perturbative gauge theories. Causal perturbation theory is a fully quantum approach: is works only with the chronological products which are defined as operator-valued distributions in the Fock space of the model. The use of causal perturbation theory leads to similar cohomology problems; the main difference with respect to the functional methods comes from the fact that the gauge transformation of the causal approach is, essentially, the linear part of the non-linear BRST transformation. Using these methods it is possible to give a nice determination of the interaction Lagrangians for gauge models (Yang-Mills and gravitation in the linear approximation); one obtains with this method the unicity of the interaction Lagrangian up to trivial terms. The case of quantum gravity is highly non-trivial and can be generalized with this method to the massive graviton case. Going to higher orders of perturbation theory one finds quantum anomalies. Again the cohomological methods can be used to determine the generic form of these anomalies. Finally, one can investigate the arbitrariness of the chronological products in higher orders and reduce this problem to cohomology methods also.

  16. Curvature constraints from the causal entropic principle

    SciTech Connect

    Bozek, Brandon; Albrecht, Andreas; Phillips, Daniel

    2009-07-15

    Current cosmological observations indicate a preference for a cosmological constant that is drastically smaller than what can be explained by conventional particle physics. The causal entropic principle (Bousso et al.) provides an alternative approach to anthropic attempts to predict our observed value of the cosmological constant by calculating the entropy created within a causal diamond. We have extended this work to use the causal entropic principle to predict the preferred curvature within the 'multiverse'. We have found that values larger than {rho}{sub k}=40{rho}{sub m} are disfavored by more than 99.99% peak value at {rho}{sub {lambda}}=7.9x10{sup -123} and {rho}{sub k}=4.3{rho}{sub m} for open universes. For universes that allow only positive curvature or both positive and negative curvature, we find a correlation between curvature and dark energy that leads to an extended region of preferred values. Our universe is found to be disfavored to an extent depending on the priors on curvature. We also provide a comparison to previous anthropic constraints on open universes and discuss future directions for this work.

  17. Causality, initial conditions, and inflationary magnetogenesis

    NASA Astrophysics Data System (ADS)

    Tsagas, Christos G.

    2016-05-01

    The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Causality implies that inflationary magnetic fields do not freeze into the matter until they have re-entered the causal horizon. The nature of the cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic magnetic decay on superhorizon scales throughout the Universe's post-inflationary evolution and thus lead to considerably stronger residual magnetic fields. This is "good news" for both the conventional and the nonconventional scenarios of cosmic magnetogenesis. Mechanisms operating outside standard electromagnetism, in particular, do not need to enhance their fields too much during inflation in order to produce seeds that can feed the galactic dynamo today. In fact, even conventionally produced inflationary magnetic fields might be able to sustain the dynamo.

  18. Reliability of the Granger causality inference

    NASA Astrophysics Data System (ADS)

    Zhou, Douglas; Zhang, Yaoyu; Xiao, Yanyang; Cai, David

    2014-04-01

    How to characterize information flows in physical, biological, and social systems remains a major theoretical challenge. Granger causality (GC) analysis has been widely used to investigate information flow through causal interactions. We address one of the central questions in GC analysis, that is, the reliability of the GC evaluation and its implications for the causal structures extracted by this analysis. Our work reveals that the manner in which a continuous dynamical process is projected or coarse-grained to a discrete process has a profound impact on the reliability of the GC inference, and different sampling may potentially yield completely opposite inferences. This inference hazard is present for both linear and nonlinear processes. We emphasize that there is a hazard of reaching incorrect conclusions about network topologies, even including statistical (such as small-world or scale-free) properties of the networks, when GC analysis is blindly applied to infer the network topology. We demonstrate this using a small-world network for which a drastic loss of small-world attributes occurs in the reconstructed network using the standard GC approach. We further show how to resolve the paradox that the GC analysis seemingly becomes less reliable when more information is incorporated using finer and finer sampling. Finally, we present strategies to overcome these inference artifacts in order to obtain a reliable GC result.

  19. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

    PubMed

    Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

    2016-03-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. PMID:25902728

  20. Developing Causal Understanding with Causal Maps: The Impact of Total Links, Temporal Flow, and Lateral Position of Outcome Nodes

    ERIC Educational Resources Information Center

    Jeong, Allan; Lee, Woon Jee

    2012-01-01

    This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…

  1. Cognitive Neuroscience and Causal Inference: Implications for Psychiatry

    PubMed Central

    Dijkstra, Nadine; de Bruin, Leon

    2016-01-01

    In this paper, we investigate to what extent it is justified to draw conclusions about causal relations between brain states and mental states from cognitive neuroscience studies. We first explain the views of two prominent proponents of the interventionist account of causation: Woodward and Baumgartner. We then discuss the implications of their views in the context of traditional cognitive neuroscience studies in which the effect of changes in mental state on changes in brain states is investigated. After this, we turn to brain stimulation studies in which brain states are manipulated to investigate the effects on mental states. We argue that, depending on whether one sides with Woodward or Baumgartner, it is possible to draw causal conclusions from both types of studies (Woodward) or from brain stimulation studies only (Baumgartner). We show what happens to these conclusions if we adopt different views of the relation between mental states and brain states. Finally, we discuss the implications of our findings for psychiatry and the treatment of psychiatric disorders. PMID:27486408

  2. Cognitive Neuroscience and Causal Inference: Implications for Psychiatry.

    PubMed

    Dijkstra, Nadine; de Bruin, Leon

    2016-01-01

    In this paper, we investigate to what extent it is justified to draw conclusions about causal relations between brain states and mental states from cognitive neuroscience studies. We first explain the views of two prominent proponents of the interventionist account of causation: Woodward and Baumgartner. We then discuss the implications of their views in the context of traditional cognitive neuroscience studies in which the effect of changes in mental state on changes in brain states is investigated. After this, we turn to brain stimulation studies in which brain states are manipulated to investigate the effects on mental states. We argue that, depending on whether one sides with Woodward or Baumgartner, it is possible to draw causal conclusions from both types of studies (Woodward) or from brain stimulation studies only (Baumgartner). We show what happens to these conclusions if we adopt different views of the relation between mental states and brain states. Finally, we discuss the implications of our findings for psychiatry and the treatment of psychiatric disorders. PMID:27486408

  3. Risk-Based Causal Modeling of Airborne Loss of Separation

    NASA Technical Reports Server (NTRS)

    Geuther, Steven C.; Shih, Ann T.

    2015-01-01

    Maintaining safe separation between aircraft remains one of the key aviation challenges as the Next Generation Air Transportation System (NextGen) emerges. The goals of the NextGen are to increase capacity and reduce flight delays to meet the aviation demand growth through the 2025 time frame while maintaining safety and efficiency. The envisioned NextGen is expected to enable high air traffic density, diverse fleet operations in the airspace, and a decrease in separation distance. All of these factors contribute to the potential for Loss of Separation (LOS) between aircraft. LOS is a precursor to a potential mid-air collision (MAC). The NASA Airspace Operations and Safety Program (AOSP) is committed to developing aircraft separation assurance concepts and technologies to mitigate LOS instances, therefore, preventing MAC. This paper focuses on the analysis of causal and contributing factors of LOS accidents and incidents leading to MAC occurrences. Mid-air collisions among large commercial aircraft are rare in the past decade, therefore, the LOS instances in this study are for general aviation using visual flight rules in the years 2000-2010. The study includes the investigation of causal paths leading to LOS, and the development of the Airborne Loss of Separation Analysis Model (ALOSAM) using Bayesian Belief Networks (BBN) to capture the multi-dependent relations of causal factors. The ALOSAM is currently a qualitative model, although further development could lead to a quantitative model. ALOSAM could then be used to perform impact analysis of concepts and technologies in the AOSP portfolio on the reduction of LOS risk.

  4. Neural Connectivity in Epilepsy as Measured by Granger Causality

    PubMed Central

    Coben, Robert; Mohammad-Rezazadeh, Iman

    2015-01-01

    Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended. PMID:26236211

  5. Temporal reasoning for diagnosis in a causal probabilistic knowledge base.

    PubMed

    Long, W

    1996-07-01

    We have added temporal reasoning to the Heart Disease Program (HDP) to take advantage of the temporal constraints inherent in cardiovascular reasoning. Some processes take place over minutes while others take place over months or years and a strictly probabilistic formalism can generate hypotheses that are impossible given the temporal relationships involved. The HDP has temporal constraints on the causal relations specified in the knowledge base and temporal properties on the patient input provided by the user. These are used in two ways. First, they are used to constrain the generation of the pre-computed causal pathways through the model that speed the generation of hypotheses. Second, they are used to generate time intervals for the instantiated nodes in the hypotheses, which are matched and adjusted as nodes are added to each evolving hypothesis. This domain offers a number of challenges for temporal reasoning. Since the nature of diagnostic reasoning is inferring a causal explanation from the evidence, many of the temporal intervals have few constraints and the reasoning has to make maximum use of those that exist. Thus, the HDP uses a temporal interval representation that includes the earliest and latest beginning and ending specified by the constraints. Some of the disease states can be corrected but some of the manifestations may remain. For example, a valve disease such as aortic stenosis produces hypertrophy that remains long after the valve has been replaced. This requires multiple time intervals to account for the existing findings. This paper discusses the issues and solutions that have been developed for temporal reasoning integrated with a pseudo-Bayesian probabilistic network in this challenging domain for diagnosis. PMID:8830922

  6. Causal contraction: spatial binding in the perception of collision events.

    PubMed

    Buehner, Marc J; Humphreys, Gruffydd R

    2010-01-01

    Causality is a higher-level mental construct derived from low-level percepts such as contiguity in space-time. We show that low-level spatial perception is distorted by the presence of a causal connection, such that two objects appear closer in space when they are causally linked than when they are not. This finding parallels recent demonstrations of temporal causal binding and suggests that causality is at the root of a general ambiguity-resolution process operating on the human perceptual system. PMID:20424021

  7. Assessing Evidence for a Common Function of Delay in Causal Learning and Reward Discounting

    PubMed Central

    Greville, W. James; Buehner, Marc J.

    2012-01-01

    Time occupies a central role in both the induction of causal relationships and determining the subjective value of rewards. Delays devalue rewards and also impair learning of relationships between events. The mathematical relation between the time until a delayed reward and its present value has been characterized as a hyperbola-like function, and increasing delays of reinforcement tend to elicit judgments or response rates that similarly show a negatively accelerated decay pattern. Furthermore, neurological research implicates both the hippocampus and prefrontal cortex in both these processes. Since both processes are broadly concerned with the concepts of reward, value, and time, involve a similar functional form, and have been identified as involving the same specific brain regions, it seems tempting to assume that the two processes are underpinned by the same cognitive or neural mechanisms. We set out to determine experimentally whether a common cognitive mechanism underlies these processes, by contrasting individual performances on causal judgment and delay discounting tasks. Results from each task corresponded with previous findings in the literature, but no relation was found between the two tasks. The task was replicated and extended by including two further measures, the Barrett Impulsiveness Scale (BIS), and a causal attribution task. Performance on this latter task was correlated with results on the causal judgment task, and also with the non-planning component of the BIS, but the results from the delay discounting task was not correlated with either causal learning task nor the BIS. Implications for current theories of learning are considered. PMID:23162508

  8. A causal model of positive health practices: the relationship between approach and replication.

    PubMed

    Yarcheski, A; Mahon, N E

    1989-01-01

    This study supports the position that causal models developed a priori preclude replication with varied samples. Based on a critique of a study of positive health practices among adults (Muhlenkamp & Sayles, 1986), a causal model of positive health practices for adolescents was developed a priori from a theoretical formulation. Using data from a sample of 165 adolescents who responded to the Personal Lifestyle Questionnaire, the Rosenberg Self-Esteem Scale, Part 2 of the Personal Resource Questionnaire which measures a social support system, and a demographic data sheet, the intercorrelations among the study variables were analyzed using correlation coefficients. The causal model was then tested with the adolescent data using the LISREL VI program. The results showed a relatively good fit of the model to the data via a number of indicators. The model was then applied to data published from adults (Muhlenkamp & Sayles) using the LISREL VI program. The results indicated that there was a relatively poor fit of the model to the adult data, thus demonstrating the problem of replicating causal models with varied samples when the correct approach to causal modeling is used. The discussion focuses on theoretical and methodological reasons for the findings. PMID:2928152

  9. Spatial convergent cross mapping to detect causal relationships from short time series.

    PubMed

    Clark, Thomas; Ye, Hao; Isbell, Forest; Deyle, Ethan R; Cowles, Jane; Tilman, G David; Sugihara, George

    2015-05-01

    Recent developments in complex systems analysis have led to new techniques for detecting causal relationships using relatively short time series, on the order of 30 sequential observations. Although many ecological observation series are even shorter, perhaps fewer than ten sequential observations, these shorter time series are often highly replicated in space (i.e., plot replication). Here, we combine the existing techniques of convergent cross mapping (CCM) and dewdrop regression to build a novel test of causal relations that leverages spatial replication, which we call multispatial CCM. Using examples from simulated and real-world ecological data, we test the ability of multispatial CCM to detect causal relationships between processes. We find that multispatial CCM successfully detects causal relationships with as few as five sequential observations, even in the presence of process noise and observation error. Our results suggest that this technique may constitute a useful test for causality in systems where experiments are difficult to perform and long time series are not available. This new technique is available in the multispatialCCM package for the R programming language. PMID:26236832

  10. Academic Procrastination: The Relationship Between Causal Attribution Styles and Behavioral Postponement

    PubMed Central

    Badri Gargari, Rahim; Sabouri, Hossein; Norzad, Fatemeh

    2011-01-01

    Objective: This research was conducted to study the relationship between attribution and academic procrastination in University Students. Methods: The subjects were 203 undergraduate students, 55 males and 148 females, selected from English and French language and literature students of Tabriz University. Data were gathered through Procrastination Assessment Scale-student (PASS) and Causal Dimension Scale (CDA) and were analyzed by multiple regression analysis (stepwise). Results: The results showed that there was a meaningful and negative relation between the locus of control and controllability in success context and academic procrastination. Besides, a meaningful and positive relation was observed between the locus of control and stability in failure context and procrastination. It was also found that 17% of the variance of procrastination was accounted by linear combination of attributions. Conclusion: We believe that causal attribution is a key in understanding procrastination in academic settings and is used by those who have the knowledge of Causal Attribution styles to organize their learning. PMID:24644450

  11. Identifying causal variants at loci with multiple signals of association.

    PubMed

    Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar

    2014-10-01

    Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515

  12. Identifying Causal Variants at Loci with Multiple Signals of Association

    PubMed Central

    Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar

    2014-01-01

    Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20–50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515

  13. Reacting to headline news: circumstances leading to causal explanations versus implicational concerns.

    PubMed

    Singh, Ramadhar; Kaur, Susheel; Junid, Fazlinda B; Self, William T

    2011-02-01

    How do people react to the headline news they receive? According to the model of people as intuitive scientists (Kelley, 1972; Ross, 1977), people-like scientists-make causal explanations (i.e., why did an event take place?) and assign responsibility to the person, the situation, or both. However, a more recently proposed social-functionalist model (Tetlock, 2002) views people less as intuitive scientists trying to understand the world and more as intuitive prosecutors trying to protect a fragile social order. Thus, implicational concerns (i.e., how would it affect people's lives, properties, and liberties?) with the news can also be likely reactions. Given the prescriptions of these models, the present authors tested the hypotheses that news reports evoke both causal explanations and implicational concerns among viewers, and that the degree of the two reactions depends on the valence (positive vs. negative) and theme (whether it is unusual or social order-linked) of the news. Singaporeans (N = 80) read one piece of headline news that represented a crossed level of valence (negative vs. positive) and theme (unusual vs. social order), and indicated the likelihood of causal explanations and implicational concerns as their first response to it. As hypothesized, positive news led to a greater likelihood of showing implicational concerns than of making causal explanations, the difference being reversed in the case of negative news; unusual news led to a greater likelihood of making causal explanations than of showing implication concerns; the likelihood of having implicational concerns with news related to social order was higher than making that of causal explanations; and the two responses were equally likely in the case of negative news. Overall, these results support a view of people as intuitive prosecutors interested in both causal explanations of and implicational concerns with a news report. PMID:22044134

  14. Causality and Causal Inference in Social Work: Quantitative and Qualitative Perspectives

    PubMed Central

    Palinkas, Lawrence A.

    2015-01-01

    Achieving the goals of social work requires matching a specific solution to a specific problem. Understanding why the problem exists and why the solution should work requires a consideration of cause and effect. However, it is unclear whether it is desirable for social workers to identify cause and effect, whether it is possible for social workers to identify cause and effect, and, if so, what is the best means for doing so. These questions are central to determining the possibility of developing a science of social work and how we go about doing it. This article has four aims: (1) provide an overview of the nature of causality; (2) examine how causality is treated in social work research and practice; (3) highlight the role of quantitative and qualitative methods in the search for causality; and (4) demonstrate how both methods can be employed to support a “science” of social work. PMID:25821393

  15. [Natural law, causality and induction: a contribution to theorectical biology].

    PubMed

    Kaspar, R

    1980-01-01

    According to the situation of recent biology it seems to be necessary to continue the theorectical foundation of this science, and especially a foundation beyond physics and metaphysics. The preconditions of such a project are given with the problems of causality, natural law and induction. The discussion of these subjects in modern philosophy of science did not bring useful results, for philosophy of science itself is orientated by physics. On the other hand even the history of these problems in biology shows that the acceptance of physical or philosophical viewpoints leads to invincible difficulties. Therefore, in this paper, I have tried to demonstrate the necessity of analyzing these basic problems in a new way. The conditions and circumstances of a biological phenomenon have a special kind of multidimensional relationship, so that they cannot be reduced to simple linear systems of cause and effect. The fact that biological systems have a lot of retroactive effects make the description of their causality much more complicated than it is in physics. So the natural law in biology is characterized by its relativity concerning the parameters which create the special dependence of a biological phenomenon's constituent parts. PMID:6781182

  16. Reichenbach on causality in 1923: Scientific inference, coordination, and confirmation.

    PubMed

    Padovani, Flavia

    2015-10-01

    In The Theory of Relativity and A Priori Knowledge (1920b), Reichenbach developed an original account of cognition as coordination of formal structures to empirical ones. One of the most salient features of this account is that it is explicitly not a top-down type of coordination, and in fact it is crucially "directed" by the empirical side. Reichenbach called this feature "the mutuality of coordination" but, in that work, did not elaborate sufficiently on how this is supposed to work. In a paper that he wrote less than two years afterwards (but that he published only in 1932), "The Principle of Causality and the Possibility of its Empirical Confirmation" (1923/1932), he described what seems to be a model for this idea, now within an analysis of causality that results in an account of scientific inference. Recent reassessments of his early proposal do not seem to capture the extent of Reichenbach's original worries. The present paper analyses Reichenbach's early account and suggests a new way to look at his early work. According to it, we perform measurements, individuate parameters, collect and analyse data, by using a "constructive" approach, such as the one with which we formulate and test hypotheses, which paradigmatically requires some simplicity assumptions. Reichenbach's attempt to account for all these aspects in 1923 was obviously limited and naive in many ways, but it shows that, in his view, there were multiple ways in which the idea of "constitution" is embodied in scientific practice. PMID:26386525

  17. Supporting inquiry learning by promoting normative understanding of multivariable causality

    NASA Astrophysics Data System (ADS)

    Keselman, Alla

    2003-11-01

    Early adolescents may lack the cognitive and metacognitive skills necessary for effective inquiry learning. In particular, they are likely to have a nonnormative mental model of multivariable causality in which effects of individual variables are neither additive nor consistent. Described here is a software-based intervention designed to facilitate students' metalevel and performance-level inquiry skills by enhancing their understanding of multivariable causality. Relative to an exploration-only group, sixth graders who practiced predicting an outcome (earthquake risk) based on multiple factors demonstrated increased attention to evidence, improved metalevel appreciation of effective strategies, and a trend toward consistent use of a controlled comparison strategy. Sixth graders who also received explicit instruction in making predictions based on multiple factors showed additional improvement in their ability to compare multiple instances as a basis for inferences and constructed the most accurate knowledge of the system. Gains were maintained in transfer tasks. The cognitive skills and metalevel understanding examined here are essential to inquiry learning.

  18. Causal Loop Analysis of coastal geomorphological systems

    NASA Astrophysics Data System (ADS)

    Payo, Andres; Hall, Jim W.; French, Jon; Sutherland, James; van Maanen, Barend; Nicholls, Robert J.; Reeve, Dominic E.

    2016-03-01

    As geomorphologists embrace ever more sophisticated theoretical frameworks that shift from simple notions of evolution towards single steady equilibria to recognise the possibility of multiple response pathways and outcomes, morphodynamic modellers are facing the problem of how to keep track of an ever-greater number of system feedbacks. Within coastal geomorphology, capturing these feedbacks is critically important, especially as the focus of activity shifts from reductionist models founded on sediment transport fundamentals to more synthesist ones intended to resolve emergent behaviours at decadal to centennial scales. This paper addresses the challenge of mapping the feedback structure of processes controlling geomorphic system behaviour with reference to illustrative applications of Causal Loop Analysis at two study cases: (1) the erosion-accretion behaviour of graded (mixed) sediment beds, and (2) the local alongshore sediment fluxes of sand-rich shorelines. These case study examples are chosen on account of their central role in the quantitative modelling of geomorphological futures and as they illustrate different types of causation. Causal loop diagrams, a form of directed graph, are used to distil the feedback structure to reveal, in advance of more quantitative modelling, multi-response pathways and multiple outcomes. In the case of graded sediment bed, up to three different outcomes (no response, and two disequilibrium states) can be derived from a simple qualitative stability analysis. For the sand-rich local shoreline behaviour case, two fundamentally different responses of the shoreline (diffusive and anti-diffusive), triggered by small changes of the shoreline cross-shore position, can be inferred purely through analysis of the causal pathways. Explicit depiction of feedback-structure diagrams is beneficial when developing numerical models to explore coastal morphological futures. By explicitly mapping the feedbacks included and neglected within a

  19. Spatial-temporal causal modeling: a data centric approach to climate change attribution (Invited)

    NASA Astrophysics Data System (ADS)

    Lozano, A. C.

    2010-12-01

    relationship) by defining a relational graph in which related locations are connected (note that this relational graph, which represents relationships among the different locations, is distinct from the causal graph, which represents causal relationships among the individual variables - e.g. temperature, pressure- within a multivariate time series). We then define a hidden Markov Random Field (hMRF), assigning a hidden state to each node (location), with the state assignment guided by the prior information encoded in the relational graph. Nodes that share the same state in the hMRF model will have the same causal graph. State assignment can thus shed light on unknown relations among locations (e.g. teleconnection). While the model has been described in terms of hard location partitioning to facilitate its exposition, in fact a soft partitioning is maintained throughout learning. This leads to a form of transfer learning, which makes our model applicable even in situations where partitioning the locations might not seem appropriate. We first validate the effectiveness of our methodology on synthetic datasets, and then apply it to actual climate measurement data. The experimental results show that our approach offers a useful alternative to the simulation-based approach for climate modeling and attribution, and has the capability to provide valuable scientific insights from a new perspective.

  20. Foundational perspectives on causality in large-scale brain networks.

    PubMed

    Mannino, Michael; Bressler, Steven L

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  1. Foundational perspectives on causality in large-scale brain networks

    NASA Astrophysics Data System (ADS)

    Mannino, Michael; Bressler, Steven L.

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  2. Investigating Effective Brain Connectivity from fMRI Data: Past Findings and Current Issues with Reference to Granger Causality Analysis

    PubMed Central

    2012-01-01

    Abstract Interactions between brain regions have been recognized as a critical ingredient required to understand brain function. Two modes of interactions have held prominence—synchronization and causal influence. Efforts to ascertain causal influence from functional magnetic resonance imaging (fMRI) data have relied primarily on confirmatory model-driven approaches, such as dynamic causal modeling and structural equation modeling, and exploratory data-driven approaches such as Granger causality analysis. A slew of recent articles have focused on the relative merits and caveats of these approaches. The relevant studies can be classified into simulations, theoretical developments, and experimental results. In the first part of this review, we will consider each of these themes and critically evaluate their arguments, with regard to Granger causality analysis. Specifically, we argue that simulations are bounded by the assumptions and simplifications made by the simulator, and hence must be regarded only as a guide to experimental design and should not be viewed as the final word. On the theoretical front, we reason that each of the improvements to existing, yet disparate, methods brings them closer to each other with the hope of eventually leading to a unified framework specifically designed for fMRI. We then review latest experimental results that demonstrate the utility and validity of Granger causality analysis under certain experimental conditions. In the second part, we will consider current issues in causal connectivity analysis—hemodynamic variability, sampling, instantaneous versus causal relationship, and task versus resting states. We highlight some of our own work regarding these issues showing the effect of hemodynamic variability and sampling on Granger causality. Further, we discuss recent techniques such as the cubature Kalman filtering, which can perform blind deconvolution of the hemodynamic response robustly well, and hence enabling wider

  3. An assessment of predominant causal factors of pilot deviations that contribute to runway incursions

    NASA Astrophysics Data System (ADS)

    Campbell, Denado M.

    The aim of this study was to identify predominant causal factors of pilot deviations in runway incursions over a two-year period. Runway incursion reports were obtained from NASA's Aviation Safety Reporting System (ASRS), and a qualitative method was used by classifying and coding each report to a specific causal factor(s). The causal factors that were used were substantiated by research from the Aircraft Owner's and Pilot's Association that found that these causal factors were the most common in runway incursion incidents and accidents. An additional causal factor was also utilized to determine the significance of pilot training in relation to runway incursions. From the reports examined, it was found that miscommunication and situational awareness have the greatest impact on pilots and are most often the major causes of runway incursions. This data can be used to assist airports, airlines, and the FAA to understand trends in pilot deviations, and to find solutions for specific problem areas in runway incursion incidents.

  4. Mendelian Randomization for the Identification of Causal Pathways in Atherosclerotic Vascular Disease.

    PubMed

    Jansen, Henning; Lieb, Wolfgang; Schunkert, Heribert

    2016-02-01

    Epidemiological and clinical studies have identified many physiological traits and biomarkers that are statistically associated with coronary artery disease (CAD). For some of these traits and biomarkers it is well established that they represent true causal risk factors for CAD. For other biomarkers, however, the distinct character of association is still a matter of debate. Randomized controlled trials (RCT) had a pivotal role in establishing causal associations between risk factors and biomarkers and CAD in some settings by demonstrating that therapeutic intervention targeting risk factors/biomarkers also affect the risk for clinical outcomes, such as CAD. In other scenarios, however, RCTs did not demonstrate clear benefits associated with lowering biomarker levels and therefore suggest that the association between these biomarkers (like C reactive protein) and CAD was driven by confounding or reverse causation. Even accurately conducted RCTs are not immune against incorrect causal inference. Moreover, the extensive costs and efforts required to conduct RCTs asked for alternative study designs to elucidate potential causal associations. Mendelian Randomization studies represent one such alternative by using genetic variants as proxies for specific biomarkers to investigate potential causal relations between biomarkers and clinical outcomes. In this review, we briefly describe the principles of MR studies and summarize recent MR studies in the context of CAD. PMID:26791863

  5. Granger Causality Network Reconstruction of Conductance-Based Integrate-and-Fire Neuronal Systems

    PubMed Central

    Zhou, Douglas; Xiao, Yanyang; Zhang, Yaoyu; Xu, Zhiqin; Cai, David

    2014-01-01

    Reconstruction of anatomical connectivity from measured dynamical activities of coupled neurons is one of the fundamental issues in the understanding of structure-function relationship of neuronal circuitry. Many approaches have been developed to address this issue based on either electrical or metabolic data observed in experiment. The Granger causality (GC) analysis remains one of the major approaches to explore the dynamical causal connectivity among individual neurons or neuronal populations. However, it is yet to be clarified how such causal connectivity, i.e., the GC connectivity, can be mapped to the underlying anatomical connectivity in neuronal networks. We perform the GC analysis on the conductance-based integrate-and-fire (IF) neuronal networks to obtain their causal connectivity. Through numerical experiments, we find that the underlying synaptic connectivity amongst individual neurons or subnetworks, can be successfully reconstructed by the GC connectivity constructed from voltage time series. Furthermore, this reconstruction is insensitive to dynamical regimes and can be achieved without perturbing systems and prior knowledge of neuronal model parameters. Surprisingly, the synaptic connectivity can even be reconstructed by merely knowing the raster of systems, i.e., spike timing of neurons. Using spike-triggered correlation techniques, we establish a direct mapping between the causal connectivity and the synaptic connectivity for the conductance-based IF neuronal networks, and show the GC is quadratically related to the coupling strength. The theoretical approach we develop here may provide a framework for examining the validity of the GC analysis in other settings. PMID:24586285

  6. Reality and causality in quantum gravity modified electrodynamics

    SciTech Connect

    Martinez, Santiago A.; Montemayor, R.; Urrutia, Luis F.

    2006-09-15

    We present a general description of the propagation properties of quantum gravity modified electrodynamics characterized by constitutive relations up to second order in the correction parameter. The effective description corresponds to an electrodynamics in a dispersive and absorptive nonlocal medium, where the Green functions and the refraction indices can be explicitly calculated. The reality of the electromagnetic field together with the requirement of causal propagation in a given reference frame leads to restrictions in the form of such refraction indices. In particular, absorption must be present in all cases and, contrary to the usual assumption, it is the dominant aspect in those effective models which exhibit linear effects in the correction parameter not related to birefringence. In such a situation absorption is linear while propagation is quadratical in the correction parameter.

  7. Causal beliefs about intellectual disability and schizophrenia and their relationship with awareness of the condition and social distance.

    PubMed

    Scior, Katrina; Furnham, Adrian

    2016-09-30

    Evidence on mental illness stigma abounds yet little is known about public perceptions of intellectual disability. This study examined causal beliefs about intellectual disability and schizophrenia and how these relate to awareness of the condition and social distance. UK lay people aged 16+(N=1752), in response to vignettes depicting intellectual disability and schizophrenia, noted their interpretation of the difficulties, and rated their agreement with 22 causal and four social distance items. They were most likely to endorse environmental causes for intellectual disability, and biomedical factors, trauma and early disadvantage for schizophrenia. Accurate identification of both vignettes was associated with stronger endorsement of biomedical causes, alongside weaker endorsement of adversity, environmental and supernatural causes. Biomedical causal beliefs and social distance were negatively correlated for intellectual disability, but not for schizophrenia. Causal beliefs mediated the relationship between identification of the condition and social distance for both conditions. While all four types of causal beliefs acted as mediators for intellectual disability, for schizophrenia only supernatural causal beliefs did. Educating the public and promoting certain causal beliefs may be of benefit in tackling intellectual disability stigma, but for schizophrenia, other than tackling supernatural attributions, may be of little benefit in reducing stigma. PMID:27376670

  8. Children's Inferential Comprehension of Pragmatic Causal Relations in Reading.

    ERIC Educational Resources Information Center

    Morgan, Argiro Louchis

    A study investigated the separate and combined effects of the syntactic organization of the sentence, the contextual framework in which a message is embedded, and the readers' past experiences on children's inferential reading comprehension of pragmatic cause/effect statements. The subjects, 144 fourth grade students, were asked to specify the…

  9. The perceived causal structures of smoking: Smoker and non-smoker comparisons.

    PubMed

    Lydon, David M; Howard, Matt C; Wilson, Stephen J; Geier, Charles F

    2016-09-01

    Despite the detrimental impact of smoking on health, its prevalence remains high. Empirical research has provided insight into the many causes and effects of smoking, yet lay perceptions of smoking remain relatively understudied. This study used a form of network analysis to gain insight into the causal attributions for smoking of both smoking and non-smoking college students. The analyses resulted in highly endorsed, complex network diagrams that conveyed the perceived causal structures of smoking. Differences in smoker and non-smoker networks emerged with smokers attributing less negative consequences to smoking behaviors. Implications for intervention are discussed. PMID:25690755

  10. Investigating the Potential Causal Relationship between Parental Knowledge and Youth Risky Behavior: A Propensity Score Analysis

    PubMed Central

    Lippold, Melissa A.; Coffman, Donna L.; Greenberg, Mark T.

    2014-01-01

    This longitudinal study aims to explore the potential causal relationship between parental knowledge and youth risky behavior among a sample of rural, early adolescents (84% White, 47% male). Using Inverse Propensity Weighting, the sample was adjusted by controlling for 33 potential confounding variables. Confounding variables include other aspects of the parent-child relationship, parental monitoring, demographic variables and earlier levels of problem behavior. The effect of parental knowledge was significant for youth substance and polysubstance use initiation, alcohol and cigarette use, attitudes towards substance use, and delinquency. Our results suggest that parental knowledge may be causally related to substance use during middle school, as the relationship between knowledge and youth outcomes remained after controlling for 33 different confounding variables. The discussion focuses on understanding issues of causality in parenting and intervention implications. PMID:24292890

  11. Investigating the potential causal relationship between parental knowledge and youth risky behavior: a propensity score analysis.

    PubMed

    Lippold, Melissa A; Coffman, Donna L; Greenberg, Mark T

    2014-12-01

    This longitudinal study aims to explore the potential causal relationship between parental knowledge and youth risky behavior among a sample of rural, early adolescents (84 % White, 47 % male). Using inverse propensity weighting, the sample was adjusted by controlling for 33 potential confounding variables. Confounding variables include other aspects of the parent-child relationship, parental monitoring, demographic variables, and earlier levels of problem behavior. The effect of parental knowledge was significant for youth substance and polysubstance use initiation, alcohol and cigarette use, attitudes towards substance use, and delinquency. Our results suggest that parental knowledge may be causally related to substance use during middle school, as the relationship between knowledge and youth outcomes remained after controlling for 33 different confounding variables. The discussion focuses on understanding issues of causality in parenting and intervention implications. PMID:24292890

  12. N250 effects for letter transpositions depend on lexicality: 'casual' or 'causal'?

    PubMed

    Duñabeitia, Jon Andoni; Molinaro, Nicola; Laka, Itziar; Estévez, Adelina; Carreiras, Manuel

    2009-03-01

    We examined the electrophysiological correlates of one of the most influential orthographic effects: the transposed-letter-masked priming effect. Transposed-letter nonword-word pairs ('jugde-judge'), as well as transposed-letter word-word pairs ('casual-causal') were included to investigate the influence of prime's lexicality in the transposed-letter effect. The results showed that when compared with the substituted-letter control conditions ('jugde-judge' vs. 'jupte-judge'), transposed-letter primes produced a lower negativity in the N250 component. In contrast, no differences were obtained between the two word-word priming conditions ('casual-causal' vs. 'carnal-causal'). The influence of lexicality in the transposed-letter effect is discussed according to the models of visual word recognition and previous evidence from event-related potentials. PMID:19248245

  13. Consistent theory for causal non-locality beyond the Born's rule

    NASA Astrophysics Data System (ADS)

    Son, Wonmin

    2014-02-01

    According to the theory of relativity and causality, a special type of correlation beyond quantum mechanics is possible in principle under the name of a non-local box. The concept has been introduced from the principle of non-locality, which satisfies relativistic causality. In this paper, we show that a correlation leading to the non-local box can be derived consistently if we release one of major axioms in quantum mechanics, Born's rule. This allows us to obtain a theory that in one end of the spectrum agrees with the classical probability and in the other end agrees with the theory of non-local causality. At the same time, we argue that the correlation lies in a space with special mathematical constraints such that a physical realization of the correlation through a probability measure is not possible in one direction of its limit, but is possible in the other limit.

  14. Learning to learn from stories: children's developing sensitivity to the causal structure of fictional worlds.

    PubMed

    Walker, Caren M; Gopnik, Alison; Ganea, Patricia A

    2015-01-01

    Fiction presents a unique challenge to the developing child, in that children must learn when to generalize information from stories to the real world. This study examines how children acquire causal knowledge from storybooks, and whether children are sensitive to how closely the fictional world resembles reality. Preschoolers (N = 108) listened to stories in which a novel causal relation was embedded within realistic or fantastical contexts. Results indicate that by at least 3 years of age, children are sensitive to the underlying causal structure of the story: Children are more likely to generalize content if the fictional world is similar to reality. Additionally, children become better able at discriminating between realistic and fantastical story contexts between 3 and 5 years of age. PMID:25156667

  15. Universal behavior of generalized causal set d’Alembertians in curved spacetime

    NASA Astrophysics Data System (ADS)

    Belenchia, Alessio

    2016-07-01

    Causal set non-local wave operators allow both for the definition of an action for causal set theory and the study of deviations from local physics that may have interesting phenomenological consequences. It was previously shown that, in all dimensions, the (unique) minimal discrete operators give averaged continuum non-local operators that reduce to \\square -R/2 in the local limit. Recently, dropping the constraint of minimality, it was shown that there exist an infinite number of discrete operators satisfying basic physical requirements and with the right local limit in flat spacetime. In this work, we consider this entire class of generalized causal set d’Alembertins in curved spacetimes and extend to them the result about the universality of the ‑R/2 factor. Finally, we comment on the relation of this result to the Einstein equivalence principle.

  16. Bulk viscosity and relaxation time of causal dissipative relativistic fluid dynamics

    NASA Astrophysics Data System (ADS)

    Huang, Xu-Guang; Kodama, Takeshi; Koide, Tomoi; Rischke, Dirk H.

    2011-02-01

    The microscopic formulas of the bulk viscosity ζ and the corresponding relaxation time τΠ in causal dissipative relativistic fluid dynamics are derived by using the projection operator method. In applying these formulas to the pionic fluid, we find that the renormalizable energy-momentum tensor should be employed to obtain consistent results. In the leading-order approximation in the chiral perturbation theory, the relaxation time is enhanced near the QCD phase transition, and τΠ and ζ are related as τΠ=ζ/[β{(1/3-cs2)(ɛ+P)-2(ɛ-3P)/9}], where ɛ, P, and cs are the energy density, pressure, and velocity of sound, respectively. The predicted ζ and τΠ should satisfy the so-called causality condition. We compare our result with the results of the kinetic calculation by Israel and Stewart and the string theory, and confirm that all three approaches are consistent with the causality condition.

  17. Identification of directed influence: Granger causality, Kullback-Leibler divergence, and complexity.

    PubMed

    Seghouane, Abd-Krim; Amari, Shun-Ichi

    2012-07-01

    Detecting and characterizing causal interdependencies and couplings between different activated brain areas from functional neuroimage time series measurements of their activity constitutes a significant step toward understanding the process of brain functions. In this letter, we make the simple point that all current statistics used to make inferences about directed influences in functional neuroimage time series are variants of the same underlying quantity. This includes directed transfer entropy, transinformation, Kullback-Leibler formulations, conditional mutual information, and Granger causality. Crucially, in the case of autoregressive modeling, the underlying quantity is the likelihood ratio that compares models with and without directed influences from the past when modeling the influence of one time series on another. This framework is also used to derive the relation between these measures of directed influence and the complexity or the order of directed influence. These results provide a framework for unifying the Kullback-Leibler divergence, Granger causality, and the complexity of directed influence. PMID:22428593

  18. Interference between Cues Requires a Causal Scenario: Favorable Evidence for Causal Reasoning Models in Learning Processes

    ERIC Educational Resources Information Center

    Luque, David; Cobos, Pedro L.; Lopez, Francisco J.

    2008-01-01

    In an interference-between-cues design (IbC), the expression of a learned Cue A-Outcome 1 association has been shown to be impaired if another cue, B, is separately paired with the same outcome in a second learning phase. The present study examined whether IbC could be caused by associative mechanisms independent of causal reasoning processes.…

  19. Causal-Explanatory Pluralism: How Intentions, Functions, and Mechanisms Influence Causal Ascriptions

    ERIC Educational Resources Information Center

    Lombrozo, Tania

    2010-01-01

    Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…

  20. Causal Inference for Spatial Constancy across Saccades.

    PubMed

    Atsma, Jeroen; Maij, Femke; Koppen, Mathieu; Irwin, David E; Medendorp, W Pieter

    2016-03-01

    Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability. PMID:26967730

  1. Super-learning of causal judgements.

    PubMed

    Aitken, M R; Larkin, M J; Dickinson, A

    2000-02-01

    In three experiments, participants learned which of a variety of foods were capable of causing an allergic reaction in a hypothetical patient during training in which a compound of a treatment and a target food cue was paired with the reaction. In Experiment 1 the causal ratings of the target cue were increased if the treatment cue was pretrained as a preventative cause of the reaction. Experiments 2 and 3 demonstrated that the magnitude of this super-learning is unaffected by the order of compound and treatment cue training. The final study also showed that forward super-learning is not induced solely by simple exposure to the treatment cue prior to compound training but, rather, depends upon training the treatment cue as a preventative cause, whereas retrospective super-learning may be due merely to exposure of the treatment cue. These results are problematic for contingency-based accounts of causal induction but accord with modified and extended associative theories. PMID:10718060

  2. Causal Drift, Robust Signaling, and Complex Disease

    PubMed Central

    Wagner, Andreas

    2015-01-01

    The phenotype of many regulatory circuits in which mutations can cause complex, polygenic diseases is to some extent robust to DNA mutations that affect circuit components. Here I demonstrate how such mutational robustness can prevent the discovery of genetic disease determinants. To make my case, I use a mathematical model of the insulin signaling pathway implicated in type 2 diabetes, whose signaling output is governed by 15 genetically determined parameters. Using multiple complementary measures of a parameter’s importance for this phenotype, I show that any one disease determinant that is crucial in one genetic background will be virtually irrelevant in other backgrounds. In an evolving population that drifts through the parameter space of this or other robust circuits through DNA mutations, the genetic changes that can cause disease will vary randomly over time. I call this phenomenon causal drift. It means that mutations causing disease in one (human or non-human) population may have no effect in another population, and vice versa. Causal drift casts doubt on our ability to infer the molecular mechanisms of complex diseases from non-human model organisms. PMID:25774510

  3. Introducing mechanics by tapping core causal knowledge

    NASA Astrophysics Data System (ADS)

    Klaassen, Kees; Westra, Axel; Emmett, Katrina; Eijkelhof, Harrie; Lijnse, Piet

    2008-07-01

    This article concerns an outline of an introductory mechanics course. It is based on the argument that various uses of the concept of force (e.g. from Kepler, Newton and everyday life) share an explanatory strategy based on core causal knowledge. The strategy consists of (a) the idea that a force causes a deviation from how an object would move of its own accord (i.e. its force-free motion), and (b) an incentive to search, where the motion deviates from the assumed force-free motion, for recurring configurations with which such deviations can be correlated (interaction theory). Various assumptions can be made concerning both the force-free motion and the interaction theory, thus giving rise to a variety of specific explanations. Kepler's semi-implicit intuition about the force-free motion is rest, Newton's explicit assumption is uniform rectilinear motion, while in everyday explanations a diversity of pragmatic suggestions can be recognized. The idea is that the explanatory strategy, once made explicit by drawing on students' intuitive causal knowledge, can be made to function for students as an advance organizer, in the sense of a general scheme that they recognize but do not yet know how to detail for scientific purposes. A previous version of this article was presented at the 2006 GIREP Conference.

  4. Causal mechanisms in airfoil-circulation formation

    NASA Astrophysics Data System (ADS)

    Zhu, J. Y.; Liu, T. S.; Liu, L. Q.; Zou, S. F.; Wu, J. Z.

    2015-12-01

    In this paper, we trace the dynamic origin, rather than any kinematic interpretations, of lift in two-dimensional flow to the physical root of airfoil circulation. We show that the key causal process is the vorticity creation by tangent pressure gradient at the airfoil surface via no-slip condition, of which the theoretical basis has been given by Lighthill ["Introduction: Boundary layer theory," in Laminar Boundary Layers, edited by L. Rosenhead (Clarendon Press, 1963), pp. 46-113], which we further elaborate. This mechanism can be clearly revealed in terms of vorticity formulation but is hidden in conventional momentum formulation, and hence has long been missing in the history of one's efforts to understand lift. By a careful numerical simulation of the flow around a NACA-0012 airfoil, and using both Eulerian and Lagrangian descriptions, we illustrate the detailed transient process by which the airfoil gains its circulation and demonstrate the dominating role of relevant dynamical causal mechanisms at the boundary. In so doing, we find that the various statements for the establishment of Kutta condition in steady inviscid flow actually correspond to a sequence of events in unsteady viscous flow.

  5. Perturbative gravity in the causal approach

    NASA Astrophysics Data System (ADS)

    Grigore, D. R.

    2010-01-01

    Quantum theory of the gravitation in the causal approach is studied up to the second order of perturbation theory in the causal approach. We emphasize the use of cohomology methods in this framework. After describing in detail the mathematical structure of the cohomology method we apply it in three different situations: (a) the determination of the most general expression of the interaction Lagrangian; (b) the proof of gauge invariance in the second order of perturbation theory for the pure gravity system—massless and massive; (c) the investigation of the arbitrariness of the second-order chronological products compatible with renormalization principles and gauge invariance (i.e. the renormalization problem in the second order of perturbation theory). In case (a) we investigate pure gravity systems and the interaction of massless gravity with matter (described by scalars and spinors) and massless Yang-Mills fields. We obtain a difference with respect to the classical field theory due to the fact that in quantum field theory one cannot enforce the divergenceless property on the vector potential and this spoils the divergenceless property of the usual energy-momentum tensor. To correct this one needs a supplementary ghost term in the interaction Lagrangian. In all three case, the computations are more simple than by the usual methods.

  6. EEG oscillations: From correlation to causality.

    PubMed

    Herrmann, Christoph S; Strüber, Daniel; Helfrich, Randolph F; Engel, Andreas K

    2016-05-01

    Already in his first report on the discovery of the human EEG in 1929, Berger showed great interest in further elucidating the functional roles of the alpha and beta waves for normal mental activities. Meanwhile, most cognitive processes have been linked to at least one of the traditional frequency bands in the delta, theta, alpha, beta, and gamma range. Although the existing wealth of high-quality correlative EEG data led many researchers to the conviction that brain oscillations subserve various sensory and cognitive processes, a causal role can only be demonstrated by directly modulating such oscillatory signals. In this review, we highlight several methods to selectively modulate neuronal oscillations, including EEG-neurofeedback, rhythmic sensory stimulation, repetitive transcranial magnetic stimulation (rTMS), and transcranial alternating current stimulation (tACS). In particular, we discuss tACS as the most recent technique to directly modulate oscillatory brain activity. Such studies demonstrating the effectiveness of tACS comprise reports on purely behavioral or purely electrophysiological effects, on combination of behavioral effects with offline EEG measurements or on simultaneous (online) tACS-EEG recordings. Whereas most tACS studies are designed to modulate ongoing rhythmic brain activity at a specific frequency, recent evidence suggests that tACS may also modulate cross-frequency interactions. Taken together, the modulation of neuronal oscillations allows to demonstrate causal links between brain oscillations and cognitive processes and to obtain important insights into human brain function. PMID:25659527

  7. Evidence for online processing during causal learning.

    PubMed

    Liu, Pei-Pei; Luhmann, Christian C

    2015-03-01

    Many models of learning describe both the end product of learning (e.g., causal judgments) and the cognitive mechanisms that unfold on a trial-by-trial basis. However, the methods employed in the literature typically provide only indirect evidence about the unfolding cognitive processes. Here, we utilized a simultaneous secondary task to measure cognitive processing during a straightforward causal-learning task. The results from three experiments demonstrated that covariation information is not subject to uniform cognitive processing. Instead, we observed systematic variation in the processing dedicated to individual pieces of covariation information. In particular, observations that are inconsistent with previously presented covariation information appear to elicit greater cognitive processing than do observations that are consistent with previously presented covariation information. In addition, the degree of cognitive processing appears to be driven by learning per se, rather than by nonlearning processes such as memory and attention. Overall, these findings suggest that monitoring learning processes at a finer level may provide useful psychological insights into the nature of learning. PMID:25488021

  8. Causal Inference for Spatial Constancy across Saccades

    PubMed Central

    Atsma, Jeroen; Maij, Femke; Koppen, Mathieu; Irwin, David E.; Medendorp, W. Pieter

    2016-01-01

    Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability. PMID:26967730

  9. A Causal Modeling Approach to the Analysis of Course Evaluation Data.

    ERIC Educational Resources Information Center

    Wolfe, Mary L.

    Five causal models relating several aspects of end-of-term student evaluation of a graduate course in nursing research methods were proposed and tested empirically. The course evaluation form consisted of four Likert-type subscales, on which students rated the following aspects of the course: (1) the extent to which the course met its objectives;…

  10. Dropouts and Turnover: The Synthesis and Test of a Causal Model of Student Attrition.

    ERIC Educational Resources Information Center

    Bean, John P.

    1980-01-01

    The determinants of student attrition in higher education institutions are investigated using a causal model which synthesized research findings on job turnover and on student attrition. Many male/female differences were found but three surrogate measures for pay were found for both sexes to be related to intent to leave. (Author/LC)

  11. The Causal Effect of Education on Health: Evidence from the United Kingdom

    ERIC Educational Resources Information Center

    Silles, Mary A.

    2009-01-01

    Numerous economic studies have shown a strong positive correlation between health and years of schooling. The question at the centre of this research is whether the correlation between health and education represents a causal relation. This paper uses changes in compulsory schooling laws in the United Kingdom to test this hypothesis. Multiple…

  12. Foreign Language Listening Anxiety and Listening Performance: Conceptualizations and Causal Relationships

    ERIC Educational Resources Information Center

    Zhang, Xian

    2013-01-01

    This study used structural equation modeling to explore the possible causal relations between foreign language (English) listening anxiety and English listening performance. Three hundred participants learning English as a foreign language (FL) completed the foreign language listening anxiety scale (FLLAS) and IELTS test twice with an interval of…

  13. Processing Inferential Causal Statements: Theoretical Refinements and the Role of Verb Type

    ERIC Educational Resources Information Center

    Mohamed, Mohamed Taha; Clifton, Charles, Jr.

    2008-01-01

    An evidential causal relation like, "Because most distinguished students got bad grades, the teacher made some mistakes in evaluating his students' papers," is more difficult to process than a factual one like, "Because he got tired after a long semester, the teacher made some mistakes in evaluating his students' papers" (Noordman & de Blijzer,…

  14. A Longitudinal Developmental Analysis of Students' Causality Beliefs about School Performance

    ERIC Educational Resources Information Center

    Roque, Isabel; de Lemos, Marina Serra; Gonçalves, Teresa

    2014-01-01

    This study examined the development of school-related causality beliefs which are children's generalized perceptions of the utility or power of different categories of specific means in producing school outcomes. Based on the action theory perspective, we analyzed the developmental model of these beliefs as well as the trajectories of the…

  15. The Effects of Time-Limitations and Peer Relationships on Adult Student Learning: A Causal Model.

    ERIC Educational Resources Information Center

    Lundberg, Carol

    Using data from 4,644 undergraduates, this study tested a causal model identifying effects of social integration, age, and time limiting characteristics on adult student learning. Time limiting characteristics included such constraints as off-campus responsibilities and relationships. Educationally related peer relationships were the strongest…

  16. Higher Education and Unemployment: A Cointegration and Causality Analysis of the Case of Turkey

    ERIC Educational Resources Information Center

    Erdem, Ekrem; Tugcu, Can Tansel

    2012-01-01

    This article analyses the short and the long-term relations between higher education and unemployment in Turkey for the period 1960-2007. It chooses the recently developed ARDL cointegration and Granger causality of Dolado and Lutkepohl (1996) methods. While the proxy of unemployment is total unemployment rate, higher education graduates were…

  17. Just Do It? Investigating the Gap between Prediction and Action in Toddlers Causal Inferences

    ERIC Educational Resources Information Center

    Bonawitz, Elizabeth Baraff; Ferranti, Darlene; Saxe, Rebecca; Gopnik, Alison; Meltzoff, Andrew N.; Woodward, James; Schulz, Laura E.

    2010-01-01

    Adults' causal representations integrate information about predictive relations and the possibility of effective intervention; if one event reliably predicts another, adults can represent the possibility that acting to bring about the first event might generate the second. Here we show that although toddlers (mean age: 24 months) readily learn…

  18. A Beta Index to Confirm Causal Directions in a Closed System of Five Variables.

    ERIC Educational Resources Information Center

    Nigro, George A.

    The beta coefficient of an intermediate variable in a causal direction remains relatively constant as other system variables are introduced and controlled in stepped regression, whereas that in the acausal direction changes noticeably. Normalized random numbers (200x5) were generated and substituted in interdependent equations to produce five…

  19. Blickets and Babies: The Development of Causal Reasoning in Toddlers and Infants

    ERIC Educational Resources Information Center

    Sobel, David M.; Kirkham, Natasha Z.

    2006-01-01

    Previous research has suggested that preschoolers possess a cognitive system that allows them to construct an abstract, coherent representation of causal relations among events. Such a system lets children reason retrospectively when they observe ambiguous data in a rational manner (e.g., D. M. Sobel, J. B. Tenenbaum, & A. Gopnik, 2004).…

  20. A Historical Overview and Contemporary Expansion of Psychological Theories of Determinism, Probabilistic Causality, Indeterminate Free Will, and Moral and Legal Responsibility

    ERIC Educational Resources Information Center

    Wilks, Duffy; Ratheal, Juli D'Ann

    2009-01-01

    The authors provide a historical overview of the development of contemporary theories of counseling and psychology in relation to determinism, probabilistic causality, indeterminate free will, and moral and legal responsibility. They propose a unique model of behavioral causality that incorporates a theory of indeterminate free will, a concept…

  1. Comparison Analysis: Granger Causality and New Causality and Their Applications to Motor Imagery.

    PubMed

    Hu, Sanqing; Wang, Hui; Zhang, Jianhai; Kong, Wanzeng; Cao, Yu; Kozma, Robert

    2016-07-01

    In this paper we first point out a fatal drawback that the widely used Granger causality (GC) needs to estimate the autoregressive model, which is equivalent to taking a series of backward recursive operations which are infeasible in many irreversible chemical reaction models. Thus, new causality (NC) proposed by Hu et al. (2011) is theoretically shown to be more sensitive to reveal true causality than GC. We then apply GC and NC to motor imagery (MI) which is an important mental process in cognitive neuroscience and psychology and has received growing attention for a long time. We study causality flow during MI using scalp electroencephalograms from nine subjects in Brain-computer interface competition IV held in 2008. We are interested in three regions: Cz (central area of the cerebral cortex), C3 (left area of the cerebral cortex), and C4 (right area of the cerebral cortex) which are considered to be optimal locations for recognizing MI states in the literature. Our results show that: 1) there is strong directional connectivity from Cz to C3/C4 during left- and right-hand MIs based on GC and NC; 2) during left-hand MI, there is directional connectivity from C4 to C3 based on GC and NC; 3) during right-hand MI, there is strong directional connectivity from C3 to C4 which is much clearly revealed by NC than by GC, i.e., NC largely improves the classification rate; and 4) NC is demonstrated to be much more sensitive to reveal causal influence between different brain regions than GC. PMID:26099149

  2. Air Pollution and Autism Spectrum Disorders: Causal or Confounded?

    PubMed

    Weisskopf, Marc G; Kioumourtzoglou, Marianthi-Anna; Roberts, Andrea L

    2015-12-01

    In the last decade, several studies have examined the association between perinatal exposure to ambient air pollution and risk of autism spectrum disorder (ASD). These studies have largely been consistent, with associations seen with different aspects of air pollution, including hazardous air toxics, ozone, particulate, and traffic-related pollution. Confounding by socioeconomic status (SES) and place of residence are of particular concern, as these can be related to ASD case ascertainment and other potential causal risk factors for ASD. While all studies take steps to address this concern, residual confounding is difficult to rule out. Two recent studies of air pollution and ASD, however, present findings that strongly argue against residual confounding, especially for factors that do not vary over relatively short time intervals. These two studies, conducted in communities around the USA, found a specific association with air pollution exposure during the 3rd, but not the 1st, trimester, when both trimesters were modeled simultaneously. In this review, we discuss confounding possibilities and then explain-with the aid of directed acyclic graphs (DAGs)-why an association that is specific to a particular time window, when multiple exposure windows are simultaneously assessed, argues against residual confounding by (even unmeasured) non-time-varying factors. In addition, we discuss why examining ambient air pollution concentration as a proxy for personal exposure helps avoid confounding by personal behavior differences, and the implications of measurement error in using ambient concentrations as a proxy for personal exposures. Given the general consistency of findings across studies and the exposure-window-specific associations recently reported, the overall evidence for a causal association between air pollution and ASD is increasingly compelling. PMID:26399256

  3. Causal inference and the hierarchical structure of experience

    PubMed Central

    Johnson, Samuel G. B.; Keil, Frank C.

    2014-01-01

    Children and adults make rich causal inferences about the physical and social world, even in novel situations where they cannot rely on prior knowledge of causal mechanisms. We propose that this capacity is supported in part by constraints provided by event structure—the cognitive organization of experience into discrete events that are hierarchically organized. These event-structured causal inferences are guided by a level-matching principle, with events conceptualized at one level of an event hierarchy causally matched to other events at that same level, and a boundary-blocking principle, with events causally matched to other events that are parts of the same superordinate event. These principles are used to constrain inferences about plausible causal candidates in unfamiliar situations, both in diagnosing causes (Experiment 1) and predicting effects (Experiment 2). The results could not be explained by construal level (Experiment 3) or similarity-matching (Experiment 4), and were robust across a variety of physical and social causal systems. Taken together, these experiments demonstrate a novel way in which non-causal information we extract from the environment can help to constrain inferences about causal structure. PMID:25347533

  4. A general, multivariate definition of causal effects in epidemiology.

    PubMed

    Flanders, W Dana; Klein, Mitchel

    2015-07-01

    Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias. PMID:25946227

  5. Comment on ``Causality-violating Higgs singlets at the LHC''

    NASA Astrophysics Data System (ADS)

    Gielen, Steffen

    2013-09-01

    The spacetime of Ho and Weiler [Phys. Rev. D 87, 045004 (2013)] supposedly admitting closed timelike curves (CTCs) is flat Minkowski spacetime with a compactified coordinate and can only contain CTCs if the compact direction is chosen to be timelike. This case of a “periodic time” is probably the simplest example of a causality-violating spacetime; it trivially satisfies all energy conditions usually assumed in general relativity, and its geodesics are just straight lines. Its relevance for phenomenology of the LHC, on the other hand, depends on consistency with observational constraints on gravity, as is mentioned in general but not discussed in any detail by Ho and Weiler. We verify a basic consistency check for stationary sources.

  6. [Prevalence and causal factors of anemia in children in Tunisia].

    PubMed

    El Ati, Jalila; Gaigi, Sadok; Beji, Chiraz; Haddad, Samira; Cherif, Samia; Farhat, Amina; Fattoum, Slaheddine; Ben Abdeladhim, Abdeladhim

    2005-09-01

    Anemia continue to be prevalent among children under five years despite the improvement of socioeconomic and sanitary indicators. The purpose of the present cross-sectorial study is to assess the etiologic factors responsible for anemia. Knowledge of the relative importance of the different causes should form a basis for intervention strategies to prevent and control anemia. The survey covered 955 children under the age of five years, native of two regions with the highest prevalent of anemia, the Southwest and the District of Tunis. The results showed that 29% of children suffered from anemia. About 70% of them were iron deficient. The fractions of the deficiency in vitamin B12 and in folates were insignificant. Only 3% of children had chronic inflammation associated with (and possibly responsible for) their anemia A little fraction of anemia (approximately 5%) was due to thalassemia or drepanocytosis. Picawasan important causal factor of iron deficiency anemia. The parasites identified instool could not cause anemia. PMID:16383194

  7. Information Causality in the Quantum and Post-Quantum Regime

    PubMed Central

    Ringbauer, Martin; Fedrizzi, Alessandro; Berry, Dominic W.; White, Andrew G.

    2014-01-01

    Quantum correlations can be stronger than anything achieved by classical systems, yet they are not reaching the limit imposed by relativity. The principle of information causality offers a possible explanation for why the world is quantum and why there appear to be no even stronger correlations. Generalizing the no-signaling condition it suggests that the amount of accessible information must not be larger than the amount of transmitted information. Here we study this principle experimentally in the classical, quantum and post-quantum regimes. We simulate correlations that are stronger than allowed by quantum mechanics by exploiting the effect of polarization-dependent loss in a photonic Bell-test experiment. Our method also applies to other fundamental principles and our results highlight the special importance of anisotropic regions of the no-signalling polytope in the study of fundamental principles. PMID:25378182

  8. Information causality in the quantum and post-quantum regime.

    PubMed

    Ringbauer, Martin; Fedrizzi, Alessandro; Berry, Dominic W; White, Andrew G

    2014-01-01

    Quantum correlations can be stronger than anything achieved by classical systems, yet they are not reaching the limit imposed by relativity. The principle of information causality offers a possible explanation for why the world is quantum and why there appear to be no even stronger correlations. Generalizing the no-signaling condition it suggests that the amount of accessible information must not be larger than the amount of transmitted information. Here we study this principle experimentally in the classical, quantum and post-quantum regimes. We simulate correlations that are stronger than allowed by quantum mechanics by exploiting the effect of polarization-dependent loss in a photonic Bell-test experiment. Our method also applies to other fundamental principles and our results highlight the special importance of anisotropic regions of the no-signalling polytope in the study of fundamental principles. PMID:25378182

  9. CauseMap: fast inference of causality from complex time series.

    PubMed

    Maher, M Cyrus; Hernandez, Ryan D

    2015-01-01

    Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data. Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM), a method for establishing causality from long time series data (≳25 observations). Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens' Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement CCM in Julia, a

  10. Equity Theory Ratios as Causal Schemas

    PubMed Central

    Arvanitis, Alexios; Hantzi, Alexandra

    2016-01-01

    Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes. PMID:27594846

  11. Causality constraints in conformal field theory

    NASA Astrophysics Data System (ADS)

    Hartman, Thomas; Jain, Sachin; Kundu, Sandipan

    2016-05-01

    Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂ ϕ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning operators.

  12. Macroscopically local correlations can violate information causality.

    PubMed

    Cavalcanti, Daniel; Salles, Alejo; Scarani, Valerio

    2010-01-01

    Although quantum mechanics is a very successful theory, its foundations are still a subject of intense debate. One of the main problems is that quantum mechanics is based on abstract mathematical axioms, rather than on physical principles. Quantum information theory has recently provided new ideas from which one could obtain physical axioms constraining the resulting statistics one can obtain in experiments. Information causality (IC) and macroscopic locality (ML) are two principles recently proposed to solve this problem. However, none of them were proven to define the set of correlations one can observe. In this study, we show an extension of IC and study its consequences. It is shown that the two above-mentioned principles are inequivalent: if the correlations allowed by nature were the ones satisfying ML, IC would be violated. This gives more confidence in IC as a physical principle, defining the possible correlation allowed by nature. PMID:21266986

  13. Equity Theory Ratios as Causal Schemas.

    PubMed

    Arvanitis, Alexios; Hantzi, Alexandra

    2016-01-01

    Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes. PMID:27594846

  14. Lightweight causal and atomic group multicast

    NASA Technical Reports Server (NTRS)

    Birman, Kenneth P.; Schiper, Andre; Stephenson, Pat

    1991-01-01

    The ISIS toolkit is a distributed programming environment based on support for virtually synchronous process groups and group communication. A suite of protocols is presented to support this model. The approach revolves around a multicast primitive, called CBCAST, which implements a fault-tolerant, causally ordered message delivery. This primitive can be used directly or extended into a totally ordered multicast primitive, called ABCAST. It normally delivers messages immediately upon reception, and imposes a space overhead proportional to the size of the groups to which the sender belongs, usually a small number. It is concluded that process groups and group communication can achieve performance and scaling comparable to that of a raw message transport layer. This finding contradicts the widespread concern that this style of distributed computing may be unacceptably costly.

  15. Assessing Thalamocortical Functional Connectivity with Granger Causality

    PubMed Central

    Israel, David; Thakor, Nitish V.; Jia, Xiaofeng

    2014-01-01

    Assessment of network connectivity across multiple brain regions is critical to understanding the mechanisms underlying various neurological disorders. Conventional methods for assessing dynamic interactions include cross-correlation and coherence analysis. However, these methods do not reveal the direction of information flow, which is important for studying the highly directional neurological system. Granger causality (GC) analysis can characterize the directional influences between two systems. We tested GC analysis for its capability to capture directional interactions within both simulated and in-vivo neural networks. The simulated networks consisted of Hindmarsh-Rose neurons; GC analysis was used to estimate the causal influences between two model networks. Our analysis successfully detected asymmetrical interactions between these networks (p<10−10, t-test). Next, we characterized the relationship between the “electrical synaptic strength” in the model networks and interactions estimated by GC analysis. We demonstrated the novel application of GC to monitor interactions between thalamic and cortical neurons following ischemia induced brain injury in a rat model of cardiac arrest (CA). We observed that during the post-CA acute period the GC interactions from the thalamus to the cortex were consistently higher than those from the cortex to the thalamus (1.983±0.278 times higher, p=0.021). In addition, the dynamics of GC interactions between the thalamus and the cortex were frequency dependent. Our study demonstrated the feasibility of GC to monitor the dynamics of thalamocortical interactions after a global nervous system injury such as CA-induced ischemia, and offers preferred alternative applications in characterizing other inter-regional interactions in an injured brain. PMID:23864221

  16. The balanced survivor average causal effect.

    PubMed

    Greene, Tom; Joffe, Marshall; Hu, Bo; Li, Liang; Boucher, Ken

    2013-01-01

    Statistical analysis of longitudinal outcomes is often complicated by the absence of observable values in patients who die prior to their scheduled measurement. In such cases, the longitudinal data are said to be "truncated by death" to emphasize that the longitudinal measurements are not simply missing, but are undefined after death. Recently, the truncation by death problem has been investigated using the framework of principal stratification to define the target estimand as the survivor average causal effect (SACE), which in the context of a two-group randomized clinical trial is the mean difference in the longitudinal outcome between the treatment and control groups for the principal stratum of always-survivors. The SACE is not identified without untestable assumptions. These assumptions have often been formulated in terms of a monotonicity constraint requiring that the treatment does not reduce survival in any patient, in conjunction with assumed values for mean differences in the longitudinal outcome between certain principal strata. In this paper, we introduce an alternative estimand, the balanced-SACE, which is defined as the average causal effect on the longitudinal outcome in a particular subset of the always-survivors that is balanced with respect to the potential survival times under the treatment and control. We propose a simple estimator of the balanced-SACE that compares the longitudinal outcomes between equivalent fractions of the longest surviving patients between the treatment and control groups and does not require a monotonicity assumption. We provide expressions for the large sample bias of the estimator, along with sensitivity analyses and strategies to minimize this bias. We consider statistical inference under a bootstrap resampling procedure. PMID:23658214

  17. Causal Inference and Model Selection in Complex Settings

    NASA Astrophysics Data System (ADS)

    Zhao, Shandong

    Propensity score methods have become a part of the standard toolkit for applied researchers who wish to ascertain causal effects from observational data. While they were originally developed for binary treatments, several researchers have proposed generalizations of the propensity score methodology for non-binary treatment regimes. In this article, we firstly review three main methods that generalize propensity scores in this direction, namely, inverse propensity weighting (IPW), the propensity function (P-FUNCTION), and the generalized propensity score (GPS), along with recent extensions of the GPS that aim to improve its robustness. We compare the assumptions, theoretical properties, and empirical performance of these methods. We propose three new methods that provide robust causal estimation based on the P-FUNCTION and GPS. While our proposed P-FUNCTION-based estimator preforms well, we generally advise caution in that all available methods can be biased by model misspecification and extrapolation. In a related line of research, we consider adjustment for posttreatment covariates in causal inference. Even in a randomized experiment, observations might have different compliance performance under treatment and control assignment. This posttreatment covariate cannot be adjusted using standard statistical methods. We review the principal stratification framework which allows for modeling this effect as part of its Bayesian hierarchical models. We generalize the current model to add the possibility of adjusting for pretreatment covariates. We also propose a new estimator of the average treatment effect over the entire population. In a third line of research, we discuss the spectral line detection problem in high energy astrophysics. We carefully review how this problem can be statistically formulated as a precise hypothesis test with point null hypothesis, why a usual likelihood ratio test does not apply for problem of this nature, and a doable fix to correctly

  18. Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects.

    PubMed

    Burgess, Stephen; Thompson, Simon G

    2015-02-15

    A conventional Mendelian randomization analysis assesses the causal effect of a risk factor on an outcome by using genetic variants that are solely associated with the risk factor of interest as instrumental variables. However, in some cases, such as the case of triglyceride level as a risk factor for cardiovascular disease, it may be difficult to find a relevant genetic variant that is not also associated with related risk factors, such as other lipid fractions. Such a variant is known as pleiotropic. In this paper, we propose an extension of Mendelian randomization that uses multiple genetic variants associated with several measured risk factors to simultaneously estimate the causal effect of each of the risk factors on the outcome. This "multivariable Mendelian randomization" approach is similar to the simultaneous assessment of several treatments in a factorial randomized trial. In this paper, methods for estimating the causal effects are presented and compared using real and simulated data, and the assumptions necessary for a valid multivariable Mendelian randomization analysis are discussed. Subject to these assumptions, we demonstrate that triglyceride-related pathways have a causal effect on the risk of coronary heart disease independent of the effects of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. PMID:25632051

  19. Multivariable Mendelian Randomization: The Use of Pleiotropic Genetic Variants to Estimate Causal Effects

    PubMed Central

    Burgess, Stephen; Thompson, Simon G.

    2015-01-01

    A conventional Mendelian randomization analysis assesses the causal effect of a risk factor on an outcome by using genetic variants that are solely associated with the risk factor of interest as instrumental variables. However, in some cases, such as the case of triglyceride level as a risk factor for cardiovascular disease, it may be difficult to find a relevant genetic variant that is not also associated with related risk factors, such as other lipid fractions. Such a variant is known as pleiotropic. In this paper, we propose an extension of Mendelian randomization that uses multiple genetic variants associated with several measured risk factors to simultaneously estimate the causal effect of each of the risk factors on the outcome. This “multivariable Mendelian randomization” approach is similar to the simultaneous assessment of several treatments in a factorial randomized trial. In this paper, methods for estimating the causal effects are presented and compared using real and simulated data, and the assumptions necessary for a valid multivariable Mendelian randomization analysis are discussed. Subject to these assumptions, we demonstrate that triglyceride-related pathways have a causal effect on the risk of coronary heart disease independent of the effects of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. PMID:25632051

  20. Edge replacement and minimality as models of causal inference in children.

    PubMed

    Buchanan, David W; Sobel, David M

    2014-01-01

    Recently, much research has focused on causal graphical models (CGMs) as a computational-level description of how children represent cause and effect. While this research program has shown promise, there are aspects of causal reasoning that CGMs have difficulty accommodating. We propose a new formalism that amends CGMs. This edge replacement grammar formalizes one existing and one novel theoretical commitment. The existing idea is that children are determinists, in the sense that they believe that apparent randomness comes from hidden complexity, rather than inherent nondeterminism in the world. The new idea is that children think of causation as a branching process: causal relations grow not directly from the cause, but from existing relations between the cause and other effects. We have shown elsewhere that these two commitments together, when formalized, can explain and quantitatively fit the otherwise puzzling effect of nonindependence observed in the adult causal reasoning literature. We then test the qualitative predictions of this new formalism on children in a series of three experiments. PMID:24851350

  1. Developmental Changes in Causal Supports for Word Learning

    ERIC Educational Resources Information Center

    Booth, Amy E.; Alvarez, Aubry

    2015-01-01

    This work explores whether the facilitative effect of causal information on preschoolers' word and descriptive fact learning persists in school-age children. Twenty-three 5-year-olds just beginning school and 23 6- to 7-year-olds who had accumulated over a year of schooling were taught novel words along with descriptions of causally rich,…

  2. Contemporary Quantitative Methods and "Slow" Causal Inference: Response to Palinkas

    ERIC Educational Resources Information Center

    Stone, Susan

    2014-01-01

    This response considers together simultaneously occurring discussions about causal inference in social work and allied health and social science disciplines. It places emphasis on scholarship that integrates the potential outcomes model with directed acyclic graphing techniques to extract core steps in causal inference. Although this scholarship…

  3. Temporal and Causal Reasoning in Deaf and Hearing Novice Readers

    ERIC Educational Resources Information Center

    Sullivan, Susan; Oakhill, Jane; Arfé, Barbara; Boureux, Magali

    2014-01-01

    Temporal and causal information in text are crucial in helping the reader form a coherent representation of a narrative. Deaf novice readers are generally poor at processing linguistic markers of causal/temporal information (i.e., connectives), but what is unclear is whether this is indicative of a more general deficit in reasoning about…

  4. Evidence for Deductive Reasoning in Blocking of Causal Judgments

    ERIC Educational Resources Information Center

    Mitchell, C.J.; Lovibond, P.F.; Condoleon, M.

    2005-01-01

    We have recently demonstrated that pre-training of additivity (the outcome of two causal cues is larger than one causal cue) greatly enhances blocking. This manipulation could work by removing a ceiling effect on the outcome, as proposed by Cheng (1997). Alternatively, it could remove the logical ambiguity associated with blocking under…

  5. From Blickets to Synapses: Inferring Temporal Causal Networks by Observation

    ERIC Educational Resources Information Center

    Fernando, Chrisantha

    2013-01-01

    How do human infants learn the causal dependencies between events? Evidence suggests that this remarkable feat can be achieved by observation of only a handful of examples. Many computational models have been produced to explain how infants perform causal inference without explicit teaching about statistics or the scientific method. Here, we…

  6. Counterfactuals and Causal Models: Introduction to the Special Issue

    ERIC Educational Resources Information Center

    Sloman, Steven A.

    2013-01-01

    Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation…

  7. Temporal and Statistical Information in Causal Structure Learning

    ERIC Educational Resources Information Center

    McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David

    2015-01-01

    Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…

  8. Individual Differences in the Neural Basis of Causal Inferencing

    ERIC Educational Resources Information Center

    Prat, Chantel S.; Mason, Robert A.; Just, Marcel Adam

    2011-01-01

    This study used fMRI to examine individual differences in the neural basis of causal inferencing. Participants with varying language skill levels, as indexed by scores on the vocabulary portion of the Nelson-Denny Reading Test, read four types of two-sentence passages in which causal relatedness (moderate and distant) and presence or absence of…

  9. Detecting Causality In Space Plasmas With Entropy Based Measures

    NASA Astrophysics Data System (ADS)

    Johnson, J. R.; Wing, S.

    2008-12-01

    Understanding causal relationships in space plasmas is a key ingredient of modeling, but can often be difficult to establish. Frequently, causality is investigated by looking at the cross-correlation and checking for a shift in the peak as a function of lag time or by examining differences in the forward and backwards directions. Some of the shortcomings of this method can be illustrated by cross-correlations that exhibit multiple peaks that are large in the non-causal direction and causal systems that do not exhibit asymmetries in the cross-correlation. Furthermore, cross-correlations only reveal linear dependency and may not be as useful for a nonlinear storage and release dynamics (such as might be expected for the magnetospheric response to the solar wind). An alternative choice for studying causality is the one-sided transfer entropy which is highly directional and accounts for static internal correlations so that it is possible to examine whether two variables are driven by a common driver or whether they are causally connected. We apply the transfer entropy to several test systems to illustrate its utility for detecting causality and to space data to illustrate causality in space systems with examples from solar wind-magnetosphere coupling.

  10. Child Care Subsidy Use and Child Development: Potential Causal Mechanisms

    ERIC Educational Resources Information Center

    Hawkinson, Laura E.

    2011-01-01

    Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…

  11. CAUSAL INFERENCE IN BIOLOGY NETWORKS WITH INTEGRATED BELIEF PROPAGATION

    PubMed Central

    CHANG, RUI; KARR, JONATHAN R; SCHADT, ERIC E

    2014-01-01

    Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the ‘fitness’ of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot. PMID:25592596

  12. The psychophysical law of speed estimation in Michotte's causal events.

    PubMed

    Parovel, Giulia; Casco, Clara

    2006-11-01

    Observers saw an event in which a computer-animated square moved up to and made contact with another, which after a short delay moved off, its motion appearing to be caused by launch by the first square. Observers chose whether the second (launched) square was faster in this causal event than when presented following a long delay (non-causal event). The speed of the second object in causal events was overestimated for a wide range of speeds of the first object (launcher), but accurately assessed in non-causal events. Experiments 2 and 3 showed that overestimation occurred also in other causal displays in which the trajectories were overlapping, successive, spatially separated or inverted but did not occurred with consecutive speeds that did not produce causal percepts. We also found that if the first object in a causal event was faster, then Weber's law holds and overestimation of the launched object speed was proportional to the speed of the launcher. In contrast, if the second object was faster, overestimation was constant, i.e. independent of the launcher. We propose that the particular speed integration of causal display results in overestimation and that the way overestimation depends on V1 phenomenally affects the attribution of the source of V2 motion: either in V1 (in launching) or in V2 (in triggering). PMID:17007898

  13. A Causal Model of Factors Influencing Faculty Use of Technology

    ERIC Educational Resources Information Center

    Meyer, Katrina A.; Xu, Yonghong Jade

    2009-01-01

    Based on earlier studies using the 1999 and 2004 National Study of Postsecondary Faculty (NSOPF) data [1, 2], a causal model explaining faculty technology use was constructed. Path analysis was used to test the causal effects of age, gender, highest degree, discipline (health science or not), recent research productivity, and teaching load on…

  14. Effect of Causal Stories in Solving Mathematical Story Problems

    ERIC Educational Resources Information Center

    Smith, Glenn Gordon; Gerretson, Helen; Olkun, Sinan; Joutsenlahti, Jorma

    2010-01-01

    This study investigated whether infusing "causal" story elements into mathematical word problems improves student performance. In one experiment in the USA and a second in USA, Finland and Turkey, undergraduate elementary education majors worked word problems in three formats: 1) standard (minimal verbiage), 2) potential causation (causal and…

  15. Forces and Motion: How Young Children Understand Causal Events

    ERIC Educational Resources Information Center

    Goksun, Tilbe; George, Nathan R.; Hirsh-Pasek, Kathy; Golinkoff, Roberta M.

    2013-01-01

    How do children evaluate complex causal events? This study investigates preschoolers' representation of "force dynamics" in causal scenes, asking whether (a) children understand how single and dual forces impact an object's movement and (b) this understanding varies across cause types (Cause, Enable, Prevent). Three-and-a half-…

  16. Seeing Versus Doing: Two Modes of Accessing Causal Knowledge

    ERIC Educational Resources Information Center

    Waldmann, Michael R.; Hagmayer, York

    2005-01-01

    The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, whose parameters were learned in a purely…

  17. Cause and Event: Supporting Causal Claims through Logistic Models

    ERIC Educational Resources Information Center

    O'Connell, Ann A.; Gray, DeLeon L.

    2011-01-01

    Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify…

  18. Causal Thinking and the Representation of Narrative Events.

    ERIC Educational Resources Information Center

    Trabasso, Tom; Van Den Broek, Paul

    1985-01-01

    Presents a comparative reanalysis of two studies into why some story events are more memorable than other events. Also proposes a theoretical account of the identified variables (story-grammar category, causal chain, causal connectivity factors to recall, and other measures of story understanding) and their influence on the comprehension of…

  19. A Probability Index of the Robustness of a Causal Inference

    ERIC Educational Resources Information Center

    Pan, Wei; Frank, Kenneth A.

    2003-01-01

    Causal inference is an important, controversial topic in the social sciences, where it is difficult to conduct experiments or measure and control for all confounding variables. To address this concern, the present study presents a probability index to assess the robustness of a causal inference to the impact of a confounding variable. The…

  20. A psychometric experiment in causal inference to estimate evidential weights used by epidemiologists.

    PubMed

    Holman, C D; Arnold-Reed, D E; de Klerk, N; McComb, C; English, D R

    2001-03-01

    A psychometric experiment in causal inference was performed on 159 Australian and New Zealand epidemiologists. Subjects each decided whether to attribute causality to 12 summaries of evidence concerning a disease and a chemical exposure. The 1,748 unique summaries embodied predetermined distributions of 19 characteristics generated by computerized evidence simulation. Effects of characteristics of evidence on causal attribution were estimated from logistic regression, and interactions were identified from a regression tree analysis. Factors with the strongest influence on the odds of causal attribution were statistical significance (odds ratio = 4.5 if 0.001 < or = P < 0.05 and 7.2 if P < 0.001, vs P > or = 0.05); refutation of alternative explanations (odds ratio = 8.1 for no known confounder vs none adjusted); strength of association (odds ratio = 2.0 if 1.5 < relative risk < or = 2.0 and 3.6 if relative risk > 2.0, vs relative risk < or = 1.5); and adjunct information concerning biological, factual, and theoretical coherence. The refutation of confounding reduced the cutpoint in the regression tree for decision-making based on strength of association. The effect of the number of supportive studies reached saturation after it exceeded 12 studies. There was evidence of flawed logic in the responses concerning specificity of effects of exposure and a tendency to discount evidence if the P-value was a "near miss" (0.050 < P < 0.065). Evidential weights based on regression coefficients for causal criteria can be applied to actual scientific evidence. PMID:11246588