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Sample records for finland granger causality

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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…

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. Analyzing multiple spike trains with nonparametric Granger causality.

    PubMed

    Nedungadi, Aatira G; Rangarajan, Govindan; Jain, Neeraj; Ding, Mingzhou

    2009-08-01

    Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation. PMID:19137420

  18. Statistical Analysis of Single-Trial Granger Causality Spectra

    PubMed Central

    Brovelli, Andrea

    2012-01-01

    Granger causality analysis is becoming central for the analysis of interactions between neural populations and oscillatory networks. However, it is currently unclear whether single-trial estimates of Granger causality spectra can be used reliably to assess directional influence. We addressed this issue by combining single-trial Granger causality spectra with statistical inference based on general linear models. The approach was assessed on synthetic and neurophysiological data. Synthetic bivariate data was generated using two autoregressive processes with unidirectional coupling. We simulated two hypothetical experimental conditions: the first mimicked a constant and unidirectional coupling, whereas the second modelled a linear increase in coupling across trials. The statistical analysis of single-trial Granger causality spectra, based on t-tests and linear regression, successfully recovered the underlying pattern of directional influence. In addition, we characterised the minimum number of trials and coupling strengths required for significant detection of directionality. Finally, we demonstrated the relevance for neurophysiology by analysing two local field potentials (LFPs) simultaneously recorded from the prefrontal and premotor cortices of a macaque monkey performing a conditional visuomotor task. Our results suggest that the combination of single-trial Granger causality spectra and statistical inference provides a valuable tool for the analysis of large-scale cortical networks and brain connectivity. PMID:22649482

  19. Nonlinear parametric model for Granger causality of time series

    NASA Astrophysics Data System (ADS)

    Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

    2006-06-01

    The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.

  20. A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity

    PubMed Central

    Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

    2016-01-01

    Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure. PMID:27064897

  1. Granger causality and cross recurrence plots in rheochaos

    NASA Astrophysics Data System (ADS)

    Ganapathy, Rajesh; Rangarajan, Govindan; Sood, A. K.

    2007-01-01

    Our stress relaxation measurements on wormlike micelles using a Rheo-SALS (rheology + small angle light scattering) apparatus allow simultaneous measurements of the stress and the scattered depolarized intensity. The latter is sensitive to orientational ordering of the micelles. To determine the presence of causal influences between the stress and the depolarized intensity time series, we have used the technique of linear and nonlinear Granger causality. We find there exists a feedback mechanism between the two time series and that the orientational order has a stronger causal effect on the stress than vice versa. We have also studied the phase space dynamics of the stress and the depolarized intensity time series using the recently developed technique of cross recurrence plots (CRPs). The presence of diagonal line structures in the CRPs unambiguously proves that the two time series share similar phase space dynamics.

  2. Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

    PubMed Central

    Kong, Wanzeng; Lin, Weicheng; Babiloni, Fabio; Hu, Sanqing; Borghini, Gianluca

    2015-01-01

    Driving fatigue has been identified as one of the main factors affecting drivers’ safety. The aim of this study was to analyze drivers’ different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers’ fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG) signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain’s ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC) in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers’ fatigue levels, and as reference work for future studies. PMID:26251909

  3. 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

  4. 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.

  5. Granger causality stock market networks: Temporal proximity and preferential attachment

    NASA Astrophysics Data System (ADS)

    Výrost, Tomáš; Lyócsa, Štefan; Baumöhl, Eduard

    2015-06-01

    The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the role of the temporal proximity between market closing times for return spillovers, i.e. the time distance between national stock markets matters. Third, a preferential attachment between stock markets exists, i.e. the probability of the presence of spillover effects between any given two markets increases with their degree of connectedness to others.

  6. The opportune time to invest in residential properties - Engle-Granger cointegration test and Granger causality test approach

    NASA Astrophysics Data System (ADS)

    Chee-Yin, Yip; Hock-Eam, Lim

    2014-12-01

    This paper examines using housing supply as proxy to house prices, the causal relationship on house prices among 8 states in Malaysia by applying the Engle-Granger cointegration test and Granger causality test approach. The target states are Perak, Selangor, Penang, Federal Territory of Kuala Lumpur (WPKL or Kuala Lumpur), Kedah, Negeri Sembilan, Sabah and Sarawak. The primary aim of this study is to estimate how long (in months) house prices in Perak lag behind that of Selangor, Penang and WPKL. We classify the 8 states into two categories - developed and developing states. We use Engle-Granger cointegration test and Granger causality test to examine the long run and short run equilibrium relationship among the two categories.. It is found that the causal relationship is bidirectional in Perak and Sabah, Perak and Selangor while it is unidirectional for Perak and Sarawak, Perak and Penang, Perak and WPKL. The speed of deviation adjustment is about 273%, suggesting that the pricing dynamic of Perak has a 32- month or 2 3/4- year lag behind that of WPKL, Selangor and Penang. Such information will be useful to investors, house buyers and speculators.

  7. 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

  8. 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

  9. Exploring Granger causality between global average observed time series of carbon dioxide and temperature

    SciTech Connect

    Kodra, Evan A; Chatterjee, Snigdhansu; Ganguly, Auroop R

    2010-01-01

    Detection and attribution methodologies have been developed over the years to delineate anthropogenic from natural drivers of climate change and impacts. A majority of prior attribution studies, which have used climate model simulations and observations or reanalysis datasets, have found evidence for humaninduced climate change. This papers tests the hypothesis that Granger causality can be extracted from the bivariate series of globally averaged land surface temperature (GT) observations and observed CO2 in the atmosphere using a reverse cumulative Granger causality test. This proposed extension of the classic Granger causality test is better suited to handle the multisource nature of the data and provides further statistical rigor. The results from this modified test show evidence for Granger causality from a proxy of total radiative forcing (RC), which in this case is a transformation of atmospheric CO2, to GT. Prior literature failed to extract these results via the standard Granger causality test. A forecasting test shows that a holdout set of GT can be better predicted with the addition of lagged RC as a predictor, lending further credibility to the Granger test results. However, since second-order-differenced RC is neither normally distributed nor variance stationary, caution should be exercised in the interpretation of our results.

  10. Functional clustering of time series gene expression data by Granger causality

    PubMed Central

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  11. 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

  12. Granger Causality Analysis of Steady-State Electroencephalographic Signals during Propofol-Induced Anaesthesia

    PubMed Central

    Barrett, Adam B.; Murphy, Michael; Bruno, Marie-Aurélie; Noirhomme, Quentin; Boly, Mélanie; Laureys, Steven; Seth, Anil K.

    2012-01-01

    Changes in conscious level have been associated with changes in dynamical integration and segregation among distributed brain regions. Recent theoretical developments emphasize changes in directed functional (i.e., causal) connectivity as reflected in quantities such as ‘integrated information’ and ‘causal density’. Here we develop and illustrate a rigorous methodology for assessing causal connectivity from electroencephalographic (EEG) signals using Granger causality (GC). Our method addresses the challenges of non-stationarity and bias by dividing data into short segments and applying permutation analysis. We apply the method to EEG data obtained from subjects undergoing propofol-induced anaesthesia, with signals source-localized to the anterior and posterior cingulate cortices. We found significant increases in bidirectional GC in most subjects during loss-of-consciousness, especially in the beta and gamma frequency ranges. Corroborating a previous analysis we also found increases in synchrony in these ranges; importantly, the Granger causality analysis showed higher inter-subject consistency than the synchrony analysis. Finally, we validate our method using simulated data generated from a model for which GC values can be analytically derived. In summary, our findings advance the methodology of Granger causality analysis of EEG data and carry implications for integrated information and causal density theories of consciousness. PMID:22242156

  13. Inference of biological networks using Bi-directional Random Forest Granger causality.

    PubMed

    Furqan, Mohammad Shaheryar; Siyal, Mohammad Yakoob

    2016-01-01

    The standard ordinary least squares based Granger causality is one of the widely used methods for detecting causal interactions between time series data. However, recent developments in technology limit the utilization of some existing implementations due to the availability of high dimensional data. In this paper, we are proposing a technique called Bi-directional Random Forest Granger causality. This technique uses the random forest regularization together with the idea of reusing the time series data by reversing the time stamp to extract more causal information. We have demonstrated the effectiveness of our proposed method by applying it to simulated data and then applied it to two real biological datasets, i.e., fMRI and HeLa cell. fMRI data was used to map brain network involved in deductive reasoning while HeLa cell dataset was used to map gene network involved in cancer. PMID:27186478

  14. 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

  15. Attribution of precipitation changes on ground-air temperature offset: Granger causality analysis

    NASA Astrophysics Data System (ADS)

    Cermak, Vladimir; Bodri, Louise

    2016-06-01

    This work examines the causal relationship between the value of the ground-air temperature offset and the precipitation changes for monitored 5-min data series together with their hourly and daily averages obtained at the Sporilov Geophysical Observatory (Prague). Shallow subsurface soil temperatures were monitored under four different land cover types (bare soil, sand, short-cut grass and asphalt). The ground surface temperature (GST) and surface air temperature (SAT) offset, ΔT(GST-SAT), is defined as the difference between the temperature measured at the depth of 2 cm below the surface and the air temperature measured at 5 cm above the surface. The results of the Granger causality test did not reveal any evidence of Granger causality for precipitation to ground-air temperature offsets on the daily scale of aggregation except for the asphalt pavement. On the contrary, a strong evidence of Granger causality for precipitation to the ground-air temperature offsets was found on the hourly scale of aggregation for all land cover types except for the sand surface cover. All results are sensitive to the lag choice of the autoregressive model. On the whole, obtained results contain valuable information on the delay time of ΔT(GST-SAT) caused by the rainfall events and confirmed the importance of using autoregressive models to understand the ground-air temperature relationship.

  16. Granger causal time-dependent source connectivity in the somatosensory network

    NASA Astrophysics Data System (ADS)

    Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M.; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

    2015-05-01

    Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

  17. Granger causal time-dependent source connectivity in the somatosensory network.

    PubMed

    Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

    2015-01-01

    Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess. PMID:25997414

  18. Granger causal time-dependent source connectivity in the somatosensory network

    PubMed Central

    Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M.; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

    2015-01-01

    Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess. PMID:25997414

  19. A Novel Extended Granger Causal Model Approach Demonstrates Brain Hemispheric Differences during Face Recognition Learning

    PubMed Central

    Ge, Tian; Kendrick, Keith M.; Feng, Jianfeng

    2009-01-01

    Two main approaches in exploring causal relationships in biological systems using time-series data are the application of Dynamic Causal model (DCM) and Granger Causal model (GCM). These have been extensively applied to brain imaging data and are also readily applicable to a wide range of temporal changes involving genes, proteins or metabolic pathways. However, these two approaches have always been considered to be radically different from each other and therefore used independently. Here we present a novel approach which is an extension of Granger Causal model and also shares the features of the bilinear approximation of Dynamic Causal model. We have first tested the efficacy of the extended GCM by applying it extensively in toy models in both time and frequency domains and then applied it to local field potential recording data collected from in vivo multi-electrode array experiments. We demonstrate face discrimination learning-induced changes in inter- and intra-hemispheric connectivity and in the hemispheric predominance of theta and gamma frequency oscillations in sheep inferotemporal cortex. The results provide the first evidence for connectivity changes between and within left and right inferotemporal cortexes as a result of face recognition learning. PMID:19936225

  20. Determination of ECoG information flow activity based on Granger causality and Hilbert transformation.

    PubMed

    Demirer, R Murat; Özerdem, Mehmet Siraç; Bayrak, Coskun; Mendi, Engin

    2013-12-01

    Analysis of directional information flow patterns among different regions of the brain is important for investigating the relation between ECoG (electrocorticographic) and mental activity. The objective is to study and evaluate the information flow activity at different frequencies in the primary motor cortex. We employed Granger causality for capturing the future state of the propagation path and direction between recording electrode sites on the cerebral cortex. A grid covered the right motor cortex completely due to its size (approx. 8 cm×8 cm) but grid area extends to the surrounding cortex areas. During the experiment, a subject was asked to imagine performing two activities: movement of the left small finger and/or movement of the tongue. The time series of the electrical brain activity was recorded during these trials using an 8×8 (0.016-300 Hz band with) ECoG platinum electrode grid, which was placed on the contralateral (right) motor cortex. For detection of information flow activity and communication frequencies among the electrodes, we have proposed a method based on following steps: (i) calculation of analytical time series such as amplitude and phase difference acquired from Hilbert transformation, (ii) selection of frequency having highest interdependence for the electrode pairs for the concerned time series over a sliding window in which we assumed time series were stationary, (iii) calculation of Granger causality values for each pair with selected frequency. The information flow (causal influence) activity and communication frequencies between the electrodes in grid were determined and shown successfully. It is supposed that information flow activity and communication frequencies between the electrodes in the grid are approximately the same for the same pattern. The successful employment of Granger causality and Hilbert transformation for the detection of the propagation path and direction of each component of ECoG among different sub

  1. 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.

  2. Prior knowledge driven Granger causality analysis on gene regulatory network discovery

    DOE PAGESBeta

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

    Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

  3. Prior knowledge driven Granger causality analysis on gene regulatory network discovery

    SciTech Connect

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

    Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, the propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.

  4. Analysis of sampling artifacts on the Granger causality analysis for topology extraction of neuronal dynamics

    PubMed Central

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

    2014-01-01

    Granger causality (GC) is a powerful method for causal inference for time series. In general, the GC value is computed using discrete time series sampled from continuous-time processes with a certain sampling interval length τ, i.e., the GC value is a function of τ. Using the GC analysis for the topology extraction of the simplest integrate-and-fire neuronal network of two neurons, we discuss behaviors of the GC value as a function of τ, which exhibits (i) oscillations, often vanishing at certain finite sampling interval lengths, (ii) the GC vanishes linearly as one uses finer and finer sampling. We show that these sampling effects can occur in both linear and non-linear dynamics: the GC value may vanish in the presence of true causal influence or become non-zero in the absence of causal influence. Without properly taking this issue into account, GC analysis may produce unreliable conclusions about causal influence when applied to empirical data. These sampling artifacts on the GC value greatly complicate the reliability of causal inference using the GC analysis, in general, and the validity of topology reconstruction for networks, in particular. We use idealized linear models to illustrate possible mechanisms underlying these phenomena and to gain insight into the general spectral structures that give rise to these sampling effects. Finally, we present an approach to circumvent these sampling artifacts to obtain reliable GC values. PMID:25126067

  5. Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality.

    PubMed

    Montalto, Alessandro; Stramaglia, Sebastiano; Faes, Luca; Tessitore, Giovanni; Prevete, Roberto; Marinazzo, Daniele

    2015-11-01

    A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments performed will show that the method presented in this work can detect the correct dynamical information flows occurring in a system of time series. Additionally we adopt a non-uniform embedding framework according to which only the past states that actually help the prediction are entered into the model, improving the prediction and avoiding the risk of overfitting. This method also leads to a further improvement with respect to traditional Granger causality approaches when redundant variables (i.e. variables sharing the same information about the future of the system) are involved. Neural networks are also able to recognize dynamics in data sets completely different from the ones used during the training phase. PMID:26356599

  6. The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

    NASA Astrophysics Data System (ADS)

    Green, J.; Lee, J. E.; Gentine, P.; Berry, J. A.; Konings, A. G.

    2015-12-01

    ABSTRACTPhotosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe. References:Beer, C., M. Reichstein, E. Tomelleri, P. Ciais, M. Jung, N. Carvalhais, C. Ro¨denbeck, M. Altaf Arain, D. Baldocchi, G. B. Bonan, A. Bondeau, A. Cescatti, G. Lasslop, A. Lindroth, M. Lomas, S. Luyssaert, H. Margolis, K. W. Oleson, O. Roupsard, E. Veenendaal, N. Viovy, C. Williams, I. Woodward, and D. Papale, 2010: Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. doi: 10.1126/science.1184984. Running, S.W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., Hashimoto, H., 2004. A Continuous Satellite Derived Measure of Global Terrestrial Primary Production. BioScience 54(6), 547-560.

  7. Effective connectivity of facial expression network by using Granger causality analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Hui; Li, Xiaoting

    2013-10-01

    Functional magnetic resonance imaging (fMRI) is an advanced non-invasive data acquisition technique to investigate the neural activity in human brain. In addition to localize the functional brain regions that is activated by specific cognitive task, fMRI can also be utilized to measure the task-related functional interactions among the active regions of interest (ROI) in the brain. Among the variety of analysis tools proposed for modeling the connectivity of brain regions, Granger causality analysis (GCA) measure the directions of information interactions by looking for the lagged effect among the brain regions. In this study, we use fMRI and Granger Causality analysis to investigate the effective connectivity of brain network induced by viewing several kinds of expressional faces. We focus on four kinds of facial expression stimuli: fearful, angry, happy and neutral faces. Five face selective regions of interest are localized and the effective connectivity within these regions is measured for the expressional faces. Our result based on 8 subjects showed that there is significant effective connectivity from STS to amygdala, from amygdala to OFA, aFFA and pFFA, from STS to aFFA and from pFFA to aFFA. This result suggested that there is an information flow from the STS to the amygdala when perusing expressional faces. This emotional expressional information flow that is conveyed by STS and amygdala, flow back to the face selective regions in occipital-temporal lobes, which constructed a emotional face processing network.

  8. 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

  9. 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

  10. Evaluating the effective connectivity of resting state networks using conditional Granger causality.

    PubMed

    Liao, Wei; Mantini, Dante; Zhang, Zhiqiang; Pan, Zhengyong; Ding, Jurong; Gong, Qiyong; Yang, Yihong; Chen, Huafu

    2010-01-01

    The human brain has been documented to be spatially organized in a finite set of specific coherent patterns, namely resting state networks (RSNs). The interactions among RSNs, being potentially dynamic and directional, may not be adequately captured by simple correlation or anticorrelation. In order to evaluate the possible effective connectivity within those RSNs, we applied a conditional Granger causality analysis (CGCA) to the RSNs retrieved by independent component analysis (ICA) from resting state functional magnetic resonance imaging (fMRI) data. Our analysis provided evidence for specific causal influences among the detected RSNs: default-mode, dorsal attention, core, central-executive, self-referential, somatosensory, visual, and auditory networks. In particular, we identified that self-referential and default-mode networks (DMNs) play distinct and crucial roles in the human brain functional architecture. Specifically, the former RSN exerted the strongest causal influence over the other RSNs, revealing a top-down modulation of self-referential mental activity (SRN) over sensory and cognitive processing. In quite contrast, the latter RSN was profoundly affected by the other RSNs, which may underlie an integration of information from primary function and higher level cognition networks, consistent with previous task-related studies. Overall, our results revealed the causal influences among these RSNs at different processing levels, and supplied information for a deeper understanding of the brain network dynamics. PMID:19937337

  11. Large-scale Granger causality analysis on resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

    2016-03-01

    We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

  12. Effect of Hemodynamic Variability on Granger Causality Analysis of fMRI

    PubMed Central

    Deshpande, Gopikrishna; Sathian, K.; Hu, Xiaoping

    2011-01-01

    In this work, we investigated the effect of the regional variability of the hemodynamic response on the sensitivity of Granger causality (GC) analysis of functional magnetic resonance imaging (fMRI) data to neuronal causal influences. We simulated fMRI data by convolving a standard canonical hemodynamic response function (HRF) with local field potentials (LFPs) acquired from the macaque cortex and manipulated the causal influence and neuronal delays between the LFPs, the hemodynamic delays between the HRFs, the signal to noise ratio (SNR) and the sampling period (TR) in order to assess the effect of each of these factors on the detectability of the neuronal delays from GC analysis of fMRI. In our first bivariate implementation, we assumed the worst case scenario of the hemodynamic delay being at the empirical upper limit of its normal physiological range and opposing the direction of neuronal delay. We found that, in the absence of HRF confounds, even tens of milliseconds of neuronal delays can be inferred from fMRI. However, in the presence of HRF delays which opposed neuronal delays, the minimum detectable neuronal delay was hundreds of milliseconds. In our second multivariate simulation, we mimicked the real situation more closely by using a multivariate network of four time series and assumed the hemodynamic and neuronal delays to be unknown and drawn from a uniform random distribution. The resulting accuracy of detecting the correct multivariate network from fMRI was well above chance and was up to 90% with faster sampling. Generically, under all conditions, faster sampling and low measurement noise improved the sensitivity of GC analysis of fMRI data to neuronal causality. PMID:20004248

  13. Detecting directional influence in fMRI connectivity analysis using PCA based Granger causality

    PubMed Central

    Zhou, Zhenyu; Ding, Mingzhou; Chen, Yonghong; Wright, Paul; Lu, Zuhong; Liu, Yijun

    2009-01-01

    A fMRI connectivity analysis approach combining both principal component analysis (PCA) and Granger causality method (GCM) is proposed to study directional influence between functional brain regions. Both simulated data and human fMRI data obtained during behavioral tasks were used to validate this method. If PCA is first used to reduce number of fMRI time series, then more energy and information features in the signal can be preserved than using averaged values from brain regions of interest. Subsequently, GCM can be applied to principal components extracted in order to further investigate effective connectivity. The simulation demonstrated that by using GCM with PCA, between-region causalities were better represented than using GCM with average values. Furthermore, after localizing an emotion task-induced activation in the anterior cingulate cortex, inferior frontal sulcus and amygdala, the directional influences among these brain regions were resolved using our new approach. These results indicate that using PCA may improve upon application of existing GCMs in study of human brain effective connectivity. PMID:19595679

  14. Correntropy-based partial directed coherence for testing multivariate Granger causality in nonlinear processes

    NASA Astrophysics Data System (ADS)

    Kannan, Rohit; Tangirala, Arun K.

    2014-06-01

    Identification of directional influences in multivariate systems is of prime importance in several applications of engineering and sciences such as plant topology reconstruction, fault detection and diagnosis, and neurosciences. A spectrum of related directionality measures, ranging from linear measures such as partial directed coherence (PDC) to nonlinear measures such as transfer entropy, have emerged over the past two decades. The PDC-based technique is simple and effective, but being a linear directionality measure has limited applicability. On the other hand, transfer entropy, despite being a robust nonlinear measure, is computationally intensive and practically implementable only for bivariate processes. The objective of this work is to develop a nonlinear directionality measure, termed as KPDC, that possesses the simplicity of PDC but is still applicable to nonlinear processes. The technique is founded on a nonlinear measure called correntropy, a recently proposed generalized correlation measure. The proposed method is equivalent to constructing PDC in a kernel space where the PDC is estimated using a vector autoregressive model built on correntropy. A consistent estimator of the KPDC is developed and important theoretical results are established. A permutation scheme combined with the sequential Bonferroni procedure is proposed for testing hypothesis on absence of causality. It is demonstrated through several case studies that the proposed methodology effectively detects Granger causality in nonlinear processes.

  15. Effective connectivity of neural pathways underlying disgust by multivariate Granger causality analysis

    NASA Astrophysics Data System (ADS)

    Yan, Hao; Wang, Yonghui; Tian, Jie; Liu, Yijun

    2011-03-01

    The disgust system arises phylogenetically in response to dangers to the internal milieu from pathogens and their toxic products. Functional imaging studies have demonstrated that a much wider range of neural structures was involved in triggering disgust reactions. However, less is known regarding how and what neural pathways these neural structures interact. To address this issue, we adopted an effective connectivity based analysis, namely the multivariate Granger causality approach, to explore the causal interactions within these brain networks. Results presented that disgust can induce a wide range of brain activities, such as the insula, the anterior cingulate cortex, the parahippocampus lobe, the dorsal lateral prefrontal cortex, the superior occipital gyrus, and the supplementary motor cortex. These brain areas constitute as a whole, with much denser connectivity following disgust stimuli, in comparison with that of the neutral condition. Moreover, the anterior insula, showing multiple casual interactions with limbic and subcortical areas, was implicated as a central hub in organizing multiple information processing in the disgust system.

  16. Investigating soil moisture feedbacks on precipitation with tests of Granger causality

    NASA Astrophysics Data System (ADS)

    Salvucci, Guido D.; Saleem, Jennifer A.; Kaufmann, Robert

    Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture ( S) feedback on precipitation ( P) using data from Illinois. In this framework S is said to Granger cause P if F(P t|Ω t- Δt )≠F(P t|Ω t- Δt -S t- Δt ) where F denotes the conditional distribution of P, Ω t- Δt represents the set of all knowledge available at time t-Δ t, and Ω t- Δt -S t- Δt represents all knowledge except S. Critical for land-atmosphere interaction research is that Ω t- Δt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed

  17. Investigating Soil Moisture Feedbacks on Precipitation With Tests of Granger Causality

    NASA Astrophysics Data System (ADS)

    Salvucci, G. D.; Saleem, J. A.; Kaufmann, R.

    2002-05-01

    Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture (S) feedback on precipitation (P) using data from Illinois. In this framework S is said to Granger cause P if F(Pt;At-dt)does not equal F(P;(A-S)t-dt) where F denotes the conditional distribution of P at time t, At-dt represents the set of all knowledge available at time t-dt, and (A-S)t-dt represents all knowledge available at t-dt except S. Critical for land-atmosphere interaction research is that At-dt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed

  18. Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

    PubMed Central

    Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

    2015-01-01

    Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

  19. Attention-Dependent Modulation of Cortical Taste Circuits Revealed by Granger Causality with Signal-Dependent Noise

    PubMed Central

    Luo, Qiang; Ge, Tian; Grabenhorst, Fabian; Feng, Jianfeng; Rolls, Edmund T.

    2013-01-01

    We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention. PMID:24204221

  20. State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI.

    PubMed

    Solo, Victor

    2016-05-01

    The recent interest in the dynamics of networks and the advent, across a range of applications, of measuring modalities that operate on different temporal scales have put the spotlight on some significant gaps in the theory of multivariate time series. Fundamental to the description of network dynamics is the direction of interaction between nodes, accompanied by a measure of the strength of such interactions. Granger causality and its associated frequency domain strength measures (GEMs) (due to Geweke) provide a framework for the formulation and analysis of these issues. In pursuing this setup, three significant unresolved issues emerge. First, computing GEMs involves computing submodels of vector time series models, for which reliable methods do not exist. Second, the impact of filtering on GEMs has never been definitively established. Third, the impact of downsampling on GEMs has never been established. In this work, using state-space methods, we resolve all these issues and illustrate the results with some simulations. Our analysis is motivated by some problems in (fMRI) brain imaging, to which we apply it, but it is of general applicability. PMID:26942749

  1. Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients

    PubMed Central

    Wang, Li; Zhang, Jingna; Zhang, Ye; Yan, Rubing; Liu, Hongliang; Qiu, Mingguo

    2016-01-01

    Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function. PMID:27200373

  2. Random forest Granger causality for detection of effective brain connectivity using high-dimensional data.

    PubMed

    Furqan, Mohammad Shaheryar; Siyal, Mohammad Yakoob

    2016-03-01

    Studies have shown that the brain functions are not localized to isolated areas and connections but rather depend on the intricate network of connections and regions inside the brain. These networks are commonly analyzed using Granger causality (GC) that utilizes the ordinary least squares (OLS) method for its standard implementation. In the past, several approaches have shown to solve the limitations of OLS by using diverse regularization systems. However, there are still some shortcomings in terms of accuracy, precision, and false discovery rate (FDR). In this paper, we are proposing a new strategy to use Random Forest as a regularization technique for computing GC that will improve these shortcomings. We have demonstrated the effectiveness of our proposed methodology by comparing the results with existing Least absolute shrinkage and selection operator (LASSO), and Elastic-Net regularized implementations of GC using simulated dataset. Later, we have used our proposed approach to map the network involved during deductive reasoning using real StarPlus dataset. PMID:26620192

  3. Lexical influences on speech perception: A Granger causality analysis of MEG and EEG source estimates

    PubMed Central

    Gow, David W.; Segawa, Jennifer A.; Ahlfors, Seppo P.; Lin, Fa-Hsuan

    2008-01-01

    Behavioural and functional imaging studies have demonstrated that lexical knowledge influences the categorization of perceptually ambiguous speech sounds. However, methodological and inferential constraints have so far been unable to resolve the question of whether this interaction takes the form of direct top-down influences on perceptual processing, or feedforward convergence during a decision process. We examined top-down lexical influences on the categorization of segments in a /s/−/∫/ continuum presented in different lexical contexts to produce a robust Ganong effect. Using integrated MEG/EEG and MRI data we found that, within a network identified by 40Hz gamma phase locking, activation in the supramarginal gyrus associated with wordform representation influences phonetic processing in the posterior superior temporal gyrus during a period of time associated with lexical processing. This result provides direct evidence that lexical processes influence lower level phonetic perception, and demonstrates the potential value of combining Granger causality analyses and high spatiotemporal resolution multimodal imaging data to explore the functional architecture of cognition. PMID:18703146

  4. Decomposing the transfer entropy to quantify lag-specific Granger causality in cardiovascular variability.

    PubMed

    Faes, Luca; Nollo, Giandomenico

    2013-01-01

    We present a modification of the well known transfer entropy (TE) which makes it able to detect, besides the direction and strength of the information transfer between coupled processes, its exact timing. The approach follows a decomposition strategy which identifies--according to a lag-specific formulation of the concept of Granger causality--the set of time delays carrying significant information, and then assigns to each of these delays an amount of information transfer such that the total contribution yields the overall TE. We propose also a procedure for the practical estimation from time series data of the relevant delays and lag-specific TE in both bivariate and multivariate settings. The proposed approach is tested in simulations and in real cardiovascular time series, showing the feasibility of lag-specific TE estimation, the ability to reflect expected mechanisms of cardiovascular regulation, and the necessity of using the multivariate TE to properly assess time-lagged information transfer in the presence of multiple interacting systems. PMID:24110870

  5. Assessing Granger Causality in Electrophysiological Data: Removing the Adverse Effects of Common Signals via Bipolar Derivations

    PubMed Central

    Trongnetrpunya, Amy; Nandi, Bijurika; Kang, Daesung; Kocsis, Bernat; Schroeder, Charles E.; Ding, Mingzhou

    2016-01-01

    Multielectrode voltage data are usually recorded against a common reference. Such data are frequently used without further treatment to assess patterns of functional connectivity between neuronal populations and between brain areas. It is important to note from the outset that such an approach is valid only when the reference electrode is nearly electrically silent. In practice, however, the reference electrode is generally not electrically silent, thereby adding a common signal to the recorded data. Volume conduction further complicates the problem. In this study we demonstrate the adverse effects of common signals on the estimation of Granger causality, which is a statistical measure used to infer synaptic transmission and information flow in neural circuits from multielectrode data. We further test the hypothesis that the problem can be overcome by utilizing bipolar derivations where the difference between two nearby electrodes is taken and treated as a representation of local neural activity. Simulated data generated by a neuronal network model where the connectivity pattern is known were considered first. This was followed by analyzing data from three experimental preparations where a priori predictions regarding the patterns of causal interactions can be made: (1) laminar recordings from the hippocampus of an anesthetized rat during theta rhythm, (2) laminar recordings from V4 of an awake-behaving macaque monkey during alpha rhythm, and (3) ECoG recordings from electrode arrays implanted in the middle temporal lobe and prefrontal cortex of an epilepsy patient during fixation. For both simulation and experimental analysis the results show that bipolar derivations yield the expected connectivity patterns whereas the untreated data (referred to as unipolar signals) do not. In addition, current source density signals, where applicable, yield results that are close to the expected connectivity patterns, whereas the commonly practiced average re-reference method

  6. Componential Granger causality, and its application to identifying the source and mechanisms of the top-down biased activation that controls attention to affective vs sensory processing.

    PubMed

    Ge, Tian; Feng, Jianfeng; Grabenhorst, Fabian; Rolls, Edmund T

    2012-01-16

    We describe a new measure of Granger causality, componential Granger causality, and show how it can be applied to the identification of the directionality of influences between brain areas with functional neuroimaging data. Componential Granger causality measures the effect of y on x, but allows interaction effects between y and x to be measured. In addition, the terms in componential Granger causality sum to 1, allowing causal effects to be directly compared between systems. We show using componential Granger causality analysis applied to an fMRI investigation that there is a top-down attentional effect from the anterior dorsolateral prefrontal cortex to the orbitofrontal cortex when attention is paid to the pleasantness of a taste, and that this effect depends on the activity in the orbitofrontal cortex as shown by the interaction term. Correspondingly there is a top-down attentional effect from the posterior dorsolateral prefrontal cortex to the insular primary taste cortex when attention is paid to the intensity of a taste, and this effect depends on the activity of the insular primary taste cortex as shown by the interaction term. Componential Granger causality thus not only can reveal the directionality of effects between areas (and these can be bidirectional), but also allows the mechanisms to be understood in terms of whether the causal influence of one system on another depends on the state of the system being causally influenced. Componential Granger causality measures the full effects of second order statistics by including variance and covariance effects between each time series, thus allowing interaction effects to be measured, and also provides a systematic framework within which to measure the effects of cross, self, and noise contributions to causality. The findings reveal some of the mechanisms involved in a biased activation theory of selective attention. PMID:21888980

  7. A conditional Granger causality model approach for group analysis in functional MRI

    PubMed Central

    Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J.; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M.; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

    2011-01-01

    Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed for identifying effective connectivity in the human brain with functional MR imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pairwise GCM has commonly been applied based on single voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of an fMRI data with GCM. To compare the effectiveness of our approach with traditional pairwise GCM models, we applied a well-established conditional GCM to pre-selected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis (ICA) of an fMRI dataset in the temporal domain. Datasets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM detected brain activation regions in the emotion related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state dataset, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network (DMN) that can be characterized as both afferent and efferent influences on the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive (MVAR) model can achieve

  8. Evaluation of net causal influences in the circuit responding to premotor control during the movement-readiness state using conditional Granger causality.

    PubMed

    Wang, Yuqing; Chen, Huafu; Gao, Qing; Yang, Yihong; Gong, Qiyong; Gao, Fabao

    2015-01-21

    As an initialization procedure for brain responding to subsequent movement execution (ME), the movement-readiness (MR) state is important for understanding the formation processes from daily movement training to long-term memory of movement pattern. As such, based on functional magnetic resonance imaging (fMRI), the net causal influences among regions contributing to premotor control during the MR state were explored by means of conditional Granger causality (CGC) and graph-theory methods in the present study. Our results found that net causal circuits responding to unimanual MR were identified during right-hand or left-hand MR, involving in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), upper precuneus (UPCU), caudate nucleus (CN), cingulate motor area (CMA), supplementary motor area (SMA) and primary sensorimotor area (S1M1). Moreover, the contralateral CN, SMA and S1M1 revealed greater net causal influences during unimanual MR, which highlighted the contralateral dominant modulations during unimanual MR. Furthermore, according as the graph-theory analysis, the higher In+Out degrees of upper precuneus (UPCU) during right-hand MR or higher In+Out degrees of cingulate motor area (CMA) and posterior cingulate cortex (PCC) during left-hand MR implied the brain asymmetry of causal connectivity in the circuit responding to right-hand or left-hand MR. This article is part of a Special Issue entitled SI: Brain and Memory. PMID:25148703

  9. Combining ICA and Granger causality: a novel tool for investigation of brain dynamics and brain oscillations using fNIRS measurements

    NASA Astrophysics Data System (ADS)

    Yuan, Zhen

    2014-03-01

    Identifying directional influences in neural circuits from functional near infrared spectroscopy (fNIRS) recordings presents one of the main challenges for understanding brain dynamics. In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes with fNIRS measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show the use of GCM in conjunction with ICA is able to effectively capture the brain network dynamics in time-frequency domain with significantly reduced computational cost. We thus suggest that the GCM-ICA technique is a potentially valuable tool that could be used for the investigation of directional causality influences of brain network dynamics in biophotonics fields.

  10. Measuring frequency domain granger causality for multiple blocks of interacting time series.

    PubMed

    Faes, Luca; Nollo, Giandomenico

    2013-04-01

    In the past years, several frequency-domain causality measures based on vector autoregressive time series modeling have been suggested to assess directional connectivity in neural systems. The most followed approaches are based on representing the considered set of multiple time series as a realization of two or three vector-valued processes, yielding the so-called Geweke linear feedback measures, or as a realization of multiple scalar-valued processes, yielding popular measures like the directed coherence (DC) and the partial DC (PDC). In the present study, these two approaches are unified and generalized by proposing novel frequency-domain causality measures which extend the existing measures to the analysis of multiple blocks of time series. Specifically, the block DC (bDC) and block PDC (bPDC) extend DC and PDC to vector-valued processes, while their logarithmic counterparts, denoted as multivariate total feedback [Formula: see text] and direct feedback [Formula: see text], represent into a full multivariate framework the Geweke's measures. Theoretical analysis of the proposed measures shows that they: (i) possess desirable properties of causality measures; (ii) are able to reflect either direct causality (bPDC, [Formula: see text] or total (direct + indirect) causality (bDC, [Formula: see text] between time series blocks; (iii) reduce to the DC and PDC measures for scalar-valued processes, and to the Geweke's measures for pairs of processes; (iv) are able to capture internal dependencies between the scalar constituents of the analyzed vector processes. Numerical analysis showed that the proposed measures can be efficiently estimated from short time series, allow to represent in an objective, compact way the information derived from the causal analysis of several pairs of time series, and may detect frequency domain causality more accurately than existing measures. The proposed measures find their natural application in the evaluation of directional

  11. Higher Education, Real Income and Real Investment in China: Evidence from Granger Causality Tests

    ERIC Educational Resources Information Center

    Narayan, Paresh Kumar; Smyth, Russell

    2006-01-01

    This paper employs cointegration and error-correction modelling to test the causal relationship between real income, real investment and tertiary education using data for the People's Republic of China over the period 1952-1999. To proxy tertiary education we use higher education enrolments and higher education graduates in alternative empirical…

  12. Observational evidence for impacts of vegetation change on local surface climate over northern China using the Granger causality test

    NASA Astrophysics Data System (ADS)

    Jiang, Bo; Liang, Shunlin; Yuan, Wenping

    2015-01-01

    three-north region in China (northeastern, northwestern, and northern China) is one of the most environmentally vulnerable regions in the country. To improve the local natural environment, the Chinese government launched the Three-North Shelter Forest Program, one of the largest afforestation/reforestation programs in the world. This program has led to significant changes in vegetation. Although many studies have evaluated the impacts of vegetation changes on local climate in this region, their results are highly inconsistent. In this study, evidence for local monthly climate impacts of vegetation change was investigated using remotely sensed data and ground meteorological measurements during the growing season (May to September) from 1982 to 2011 using the bivariate Granger causality test. The results showed that the local near-surface climate is sensitive mostly to vegetation changes characterized by the normalized difference vegetation index (NDVI) in arid and semiarid regions and that vegetation plays a more important role in influencing hydroclimate in the arid/semiarid zones than in other zones, which has great implications for water resources in this dry region. Moreover, NDVI changes in northeastern China have a significantly negative influence on air tembut no other climatic variables, whereas the test results in northern China is not as objective as the other zones due to the rapid urbanization. All these results suggest that the local climate is very sensitive to the variations in vegetation in arid and semiarid regions, so extra caution should be taken when planting trees in this area.

  13. Parkinson subtype-specific Granger-causal coupling and coherence frequency in the subthalamic area.

    PubMed

    Florin, Esther; Pfeifer, Johannes; Visser-Vandewalle, Veerle; Schnitzler, Alfons; Timmermann, Lars

    2016-09-22

    Previous work on Parkinson's disease (PD) has indicated a predominantly afferent coupling between affected arm muscle activity and electrophysiological activity within the subthalamic nucleus (STN). So far, no information is available indicating which frequency components drive the afferent information flow in PD patients. Non-directional coupling e.g. by measuring coherence is primarily established in the beta band as well as at tremor frequency. Based on previous evidence it is likely that different subtypes of the disease are associated with different connectivity patterns. Therefore, we determined coherence and causality between local field potentials (LFPs) in the STN and surface electromyograms (EMGs) from the contralateral arm in 18 akinetic-rigid (AR) PD patients and 8 tremor-dominant (TD) PD patients. During the intraoperative recording, patients were asked to lift their forearm contralateral to the recording side. Significantly more afferent connections were detected for the TD patients for tremor-periods and non-tremor-periods combined as well as for only tremor periods. Within the STN 74% and 63% of the afferent connections are associated with coherence from 4-8Hz and 8-12Hz, respectively. However, when considering only tremor-periods significantly more afferent than efferent connections were associated with coherence from 12 to 20Hz across all recording heights. No difference between efferent and afferent connections is seen in the frequency range from 4 to 12Hz for all recording heights. For the AR patients, no significant difference in afferent and efferent connections within the STN was found for the different frequency bands. Still, for the AR patients dorsal of the STN significantly more afferent than efferent connections were associated with coherence in the frequency range from 12 to 16Hz. These results provide further evidence for the differential pathological oscillations and pathways present in AR and TD Parkinson patients. PMID:27393252

  14. Theta-rhythmic drive between medial septum and hippocampus in slow-wave sleep and microarousal: a Granger causality analysis.

    PubMed

    Kang, D; Ding, M; Topchiy, I; Shifflett, L; Kocsis, B

    2015-11-01

    Medial septum (MS) plays a critical role in controlling the electrical activity of the hippocampus (HIPP). In particular, theta-rhythmic burst firing of MS neurons is thought to drive lasting HIPP theta oscillations in rats during waking motor activity and REM sleep. Less is known about MS-HIPP interactions in nontheta states such as non-REM sleep, in which HIPP theta oscillations are absent but theta-rhythmic burst firing in subsets of MS neurons is preserved. The present study used Granger causality (GC) to examine the interaction patterns between MS and HIPP in slow-wave sleep (SWS, a nontheta state) and during its short interruptions called microarousals (a transient theta state). We found that during SWS, while GC revealed a unidirectional MS→HIPP influence over a wide frequency band (2-12 Hz, maximum: ∼8 Hz), there was no theta peak in the hippocampal power spectra, indicating a lack of theta activity in HIPP. In contrast, during microarousals, theta peaks were seen in both MS and HIPP power spectra and were accompanied by bidirectional GC with MS→HIPP and HIPP→MS theta drives being of equal magnitude. Thus GC in a nontheta state (SWS) vs. a theta state (microarousal) primarily differed in the level of HIPP→MS. The present findings suggest a modification of our understanding of the role of MS as the theta generator in two regards. First, a MS→HIPP theta drive does not necessarily induce theta field oscillations in the hippocampus, as found in SWS. Second, HIPP theta oscillations entail bidirectional theta-rhythmic interactions between MS and HIPP. PMID:26354315

  15. Lexical mediation of phonotactic frequency effects on spoken word recognition: A Granger causality analysis of MRI-constrained MEG/EEG data

    PubMed Central

    Gow, David W.; Olson, Bruna B.

    2015-01-01

    Phonotactic frequency effects play a crucial role in a number of debates over language processing and representation. It is unclear however, whether these effects reflect prelexical sensitivity to phonotactic frequency, or lexical “gang effects” in speech perception. In this paper, we use Granger causality analysis of MR-constrained MEG/EEG data to understand how phonotactic frequency influences neural processing dynamics during auditory lexical decision. Effective connectivity analysis showed weaker feedforward influence from brain regions involved in acoustic-phonetic processing (superior temporal gyrus) to lexical areas (supramarginal gyrus) for high phonotactic frequency words, but stronger top-down lexical influence for the same items. Low entropy nonwords (nonwords judged to closely resemble real words) showed a similar pattern of interactions between brain regions involved in lexical and acoustic-phonetic processing. These results contradict the predictions of a feedforward model of phonotactic frequency facilitation, but support the predictions of a lexically mediated account. PMID:25883413

  16. Investigating neural primacy in Major Depressive Disorder: Multivariate granger causality analysis of resting-state fMRI time-series data

    PubMed Central

    Hamilton, J. Paul; Chen, Gang; Thomason, Moriah E.; Schwartz, Mirra E.; Gotlib, Ian H.

    2010-01-01

    Major Depressive Disorder (MDD) has been conceptualized as a neural network-level disease. Few studies of the neural bases of depression, however, have used analytic techniques that are capable of testing network-level hypotheses of neural dysfunction in this disorder. Moreover, of those that have, fewer still have attempted to determine directionality of influence within functionally abnormal networks of structures. We used multivariate Granger causality analysis — a technique that estimates the extent to which preceding neural activity in one or more seed regions predicts subsequent activity in target brain regions — to analyze blood-oxygen-level dependent (BOLD) data collected during eyes-closed rest in depressed and never-depressed persons. We found that activation in the hippocampus predicted subsequent increases in ventral anterior cingulate cortex (vACC) activity in depression, and that activity in medial prefrontal cortex and vACC were mutually reinforcing in MDD. Hippocampal and vACC activation in depressed participants predicted subsequent decreases in dorsal cortical activity. This study shows that, on a moment-by-moment basis, there is increased excitatory activity among limbic and paralimbic structures, as well as increased inhibition in activity of dorsal cortical structures, by limbic structures in depression; these aberrant patterns of effective connectivity implicate disturbances in the mesostriatal dopamine system in depression. These findings advance neural theory of depression by detailing specific patterns of limbic excitation in MDD, by making explicit the primary role of limbic inhibition of dorsal cortex in the cortico-limbic relation posited to underlie depression, and by presenting an integrated neurofunctional account of altered dopamine function in this disorder. PMID:20479758

  17. Globally conditioned Granger causality in brain-brain and brain-heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study.

    PubMed

    Duggento, Andrea; Bianciardi, Marta; Passamonti, Luca; Wald, Lawrence L; Guerrisi, Maria; Barbieri, Riccardo; Toschi, Nicola

    2016-05-13

    The causal, directed interactions between brain regions at rest (brain-brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain-heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain-brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain-brain and brain-heart interactions reflecting

  18. Wiener-Granger causality for effective connectivity in the hidden states: Indication from probabilistic causality. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

    NASA Astrophysics Data System (ADS)

    Tang, Wei

    2015-12-01

    Statistics and probability theory have advanced our understanding of random processes widely observed in the physical world. There is a remarkable trend in studying the brain by looking into the stochastic information processing in large-scale brain networks [1,2]. As the review by Mannino and Bressler [3] points out, the probabilistic notion of causality, with its rooted philosophical foundations, represents a revolutionary view on how different parts of the brain interact and integrate to generate function. Specifically, Probabilistic Causality (PC) asserts that a cause should increase the probability of occurrence of its effect, and PC between two brain regions entails that the probability for the activity in one region to occur increases when conditioned on the activity of the other. This definition claims inherent randomness in the causal relationship.

  19. Finland.

    PubMed

    1986-10-01

    In 1985, Finland's population stood at 4,913,300, with an annual growth rate of 0.35%. The 1984 infant mortality rate was 6.6/1000 and life expectancy was 70.4 years for males and 78.8 years for females. Finland's literacy rate approaches 100%. Of the labor force of 2,437,000, 11.5% are engaged in agriculture; 45.5% are employed in industry, commerce, and finance; 28% are in the service sector; 5.1% work for the government; and 7.6% work in the transport sector. The gross domestic product (GDP) was US$54 billion in 1985, with an annual growth rate of 2.8% and a per capita income of $1,007. Industry accounts for 28% of the GDP. An extensive social welfare system, comprising 20% of the national income, includes a variety of pension and assistance programs and a comprehensive health insurance program covering the entire Finnish population. Finland's proportional representation system of government encourages a multitude of political parties and has resulted in several coalition governments. Finland's industrial economy is based on capital investment and new technology. PMID:12178064

  20. Granger causality from changes in level of atmospheric CO2 to global surface temperature and the El Niño-Southern Oscillation, and a candidate mechanism in global photosynthesis

    NASA Astrophysics Data System (ADS)

    Leggett, L. M. W.; Ball, D. A.

    2015-10-01

    A significant difference, now of some 16 years' duration, has been shown to exist between the observed global surface temperature trend and that expected from the majority of climate simulations. For its own sake, and to enable better climate prediction for policy use, the reasons behind this mismatch need to be better understood. While an increasing number of possible causes have been proposed, the candidate causes have not yet converged. With this background, this paper reinvestigates the relationship between change in the level of CO2 and two of the major climate variables, atmospheric temperature and the El Niño-Southern Oscillation (ENSO). Using time-series analysis in the form of dynamic regression modelling with autocorrelation correction, it is shown that first-difference CO2 leads temperature and that there is a highly statistically significant correlation between first-difference CO2 and temperature. Further, a correlation is found for second-difference CO2 with the Southern Oscillation Index, the atmospheric-pressure component of ENSO. This paper also shows that both these correlations display Granger causality. It is shown that the first-difference CO2 and temperature model shows no trend mismatch in recent years. These results may contribute to the prediction of future trends for global temperature and ENSO. Interannual variability in the growth rate of atmospheric CO2 is standardly attributed to variability in the carbon sink capacity of the terrestrial biosphere. The terrestrial biosphere carbon sink is created by the difference between photosynthesis and respiration (net primary productivity): a major way of measuring global terrestrial photosynthesis is by means of satellite measurements of vegetation reflectance, such as the Normalized Difference Vegetation Index (NDVI). In a preliminary analysis, this study finds a close correlation between an increasing NDVI and the increasing climate model/temperature mismatch (as quantified by the difference

  1. 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.

  2. Parallel versus Serial Processing Dependencies in the Perisylvian Speech Network: A Granger Analysis of Intracranial EEG Data

    ERIC Educational Resources Information Center

    Gow, David W., Jr.; Keller, Corey J.; Eskandar, Emad; Meng, Nate; Cash, Sydney S.

    2009-01-01

    In this work, we apply Granger causality analysis to high spatiotemporal resolution intracranial EEG (iEEG) data to examine how different components of the left perisylvian language network interact during spoken language perception. The specific focus is on the characterization of serial versus parallel processing dependencies in the dominant…

  3. Multiscale causal connectivity analysis by canonical correlation: theory and application to epileptic brain.

    PubMed

    Wu, Guo Rong; Chen, Fuyong; Kang, Dezhi; Zhang, Xiangyang; Marinazzo, Daniele; Chen, Huafu

    2011-11-01

    Multivariate Granger causality is a well-established approach for inferring information flow in complex systems, and it is being increasingly applied to map brain connectivity. Traditional Granger causality is based on vector autoregressive (AR) or mixed autoregressive moving average (ARMA) model, which are potentially affected by errors in parameter estimation and may be contaminated by zero-lag correlation, notably when modeling neuroimaging data. To overcome this issue, we present here an extended canonical correlation approach to measure multivariate Granger causal interactions among time series. The procedure includes a reduced rank step for calculating canonical correlation analysis (CCA), and extends the definition of causality including instantaneous effects, thus avoiding the potential estimation problems of AR (or ARMA) models. We tested this approach on simulated data and confirmed its practical utility by exploring local network connectivity at different scales in the epileptic brain analyzing scalp and depth-EEG data during an interictal period. PMID:21788178

  4. Membership Finland

    ScienceCinema

    None

    2011-04-25

    Le DG C.Rubbia et la vice présidente du conseil du Cern souhaite la bienvenue à l'adhésion de la Finlande, comme 15me membre du Cern depuis le 1. janvier 1991 en présence du secrétaire generale et de l'ambassadeur

  5. 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

  6. 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

  7. A Nonlinear Causality Estimator Based on Non-Parametric Multiplicative Regression

    PubMed Central

    Nicolaou, Nicoletta; Constandinou, Timothy G.

    2016-01-01

    Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, CNPMR, Autoregressive modeling is replaced by Nonparametric Multiplicative Regression (NPMR). NPMR quantifies interactions between a response variable (effect) and a set of predictor variables (cause); here, we modified NPMR for model prediction. We also demonstrate how a particular measure, the sensitivity Q, could be used to reveal the structure of the underlying causal relationships. We apply CNPMR on artificial data with known ground truth (5 datasets), as well as physiological data (2 datasets). CNPMR correctly identifies both linear and nonlinear causal connections that are present in the artificial data, as well as physiologically relevant connectivity in the real data, and does not seem to be affected by filtering. The Sensitivity measure also provides useful information about the latent connectivity.The proposed estimator addresses many of the limitations of linear Granger causality and other nonlinear causality estimators. CNPMR is compared with pairwise and conditional Granger causality (linear) and Kernel-Granger causality (nonlinear). The proposed estimator can be applied to pairwise or multivariate estimations without any modifications to the main method. Its nonpametric nature, its ability to capture nonlinear relationships and its robustness to filtering make it appealing for a number of applications. PMID:27378901

  8. Education and Economic Growth in Pakistan: A Cointegration and Causality Analysis

    ERIC Educational Resources Information Center

    Afzal, Muhammad; Rehman, Hafeez Ur; Farooq, Muhammad Shahid; Sarwar, Kafeel

    2011-01-01

    This study explored the cointegration and causality between education and economic growth in Pakistan by using time series data on real gross domestic product (RGDP), labour force, physical capital and education from 1970-1971 to 2008-2009 were used. Autoregressive Distributed Lag (ARDL) Model of Cointegration and the Augmented Granger Causality…

  9. 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…

  10. 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…

  11. 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

  12. 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.

  13. New Levels of Language Processing Complexity and Organization Revealed by Granger Causation

    PubMed Central

    Gow, David W.; Caplan, David N.

    2012-01-01

    Granger causation analysis of high spatiotemporal resolution reconstructions of brain activation offers a new window on the dynamic interactions between brain areas that support language processing. Premised on the observation that causes both precede and uniquely predict their effects, this approach provides an intuitive, model-free means of identifying directed causal interactions in the brain. It requires the analysis of all non-redundant potentially interacting signals, and has shown that even “early” processes such as speech perception involve interactions of many areas in a strikingly large network that extends well beyond traditional left hemisphere perisylvian cortex that play out over hundreds of milliseconds. In this paper we describe this technique and review several general findings that reframe the way we think about language processing and brain function in general. These include the extent and complexity of language processing networks, the central role of interactive processing dynamics, the role of processing hubs where the input from many distinct brain regions are integrated, and the degree to which task requirements and stimulus properties influence processing dynamics and inform our understanding of “language-specific” localized processes. PMID:23293611

  14. 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

  15. 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

  16. 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

  17. 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

  18. Adult Education in Finland

    ERIC Educational Resources Information Center

    Szekely, Radu

    2006-01-01

    Ever since the first ideas of national independence appeared in Finland, adult education has played an essential role in shaping the destiny of the Finns. With a history of almost 130 years, during which it has continuously increased in quality and quantity, the Finnish adult education system has ensured that Finland stays among the most…

  19. 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.

  20. The causal relationship between subcortical local field potential oscillations and Parkinsonian resting tremor

    NASA Astrophysics Data System (ADS)

    Tass, Peter; Smirnov, Dmitry; Karavaev, Anatoly; Barnikol, Utako; Barnikol, Thomas; Adamchic, Ilya; Hauptmann, Christian; Pawelcyzk, Norbert; Maarouf, Mohammad; Sturm, Volker; Freund, Hans-Joachim; Bezruchko, Boris

    2010-02-01

    To study the dynamical mechanism which generates Parkinsonian resting tremor, we apply coupling directionality analysis to local field potentials (LFP) and accelerometer signals recorded in an ensemble of 48 tremor epochs in four Parkinsonian patients with depth electrodes implanted in the ventro-intermediate nucleus of the thalamus (VIM) or the subthalmic nucleus (STN). Apart from the traditional linear Granger causality method we use two nonlinear techniques: phase dynamics modelling and nonlinear Granger causality. We detect a bidirectional coupling between the subcortical (VIM or STN) oscillation and the tremor, in the theta range (around 5 Hz) as well as broadband (>2 Hz). In particular, we show that the theta band LFP oscillations definitely play an efferent role in tremor generation, while beta band LFP oscillations might additionally contribute. The brain→tremor driving is a complex, nonlinear mechanism, which is reliably detected with the two nonlinear techniques only. In contrast, the tremor→brain driving is detected with any of the techniques including the linear one, though the latter is less sensitive. The phase dynamics modelling (applied to theta band oscillations) consistently reveals a long delay in the order of 1-2 mean tremor periods for the brain→tremor driving and a small delay, compatible with the neural transmission time, for the proprioceptive feedback. Granger causality estimation (applied to broadband signals) does not provide reliable estimates of the delay times, but is even more sensitive to detect the brain→tremor influence than the phase dynamics modelling.

  1. Causal Predominance of Cognitions in Disturbed Affects among Finnish Primary School Teachers.

    ERIC Educational Resources Information Center

    Rajala, Raimo

    1990-01-01

    A putative causal relationship of cognitions to affects in different phases of teachers' stress cycles was studied for 414 elementary school teachers in Finland. Results provide only negligible support for the causal predominance of cognitions in disturbed affects; the opposite seemed to prevail. Implications for teacher satisfaction are…

  2. Finland's Cleanup Campaign

    ERIC Educational Resources Information Center

    Environmental Science and Technology, 1975

    1975-01-01

    Finland has received a $20 million loan from the World Bank to attack its pollution problems, mainly water. Improved quality of life, as well as resource conservation are both motives and goals of that country's environmental programs. (BT)

  3. 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

  4. Finland to Join ESO

    NASA Astrophysics Data System (ADS)

    2004-03-01

    Finland will become the eleventh member state of the European Southern Observatory. In a ceremony at the ESO Headquarters in Garching on 9 February 2004, an Agreement to this effect was signed by the Finnish Minister of Education and Science, Ms. Tuula Haatainen and the ESO Director General, Dr. Catherine Cesarsky, in the presence of other high officials from Finland and the ESO member states.

  5. Stochastic causality, criticality, and non-locality in brain networks. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

    NASA Astrophysics Data System (ADS)

    Kozma, Robert; Hu, Sanqing

    2015-12-01

    For millennia, causality served as a powerful guiding principle to our understanding of natural processes, including the functioning of our body, mind, and brain. The target paper presents an impressive vista of the field of causality in brain networks, starting from philosophical issues, expanding on neuroscience effects, and addressing broad engineering and societal aspects as well. The authors conclude that the concept of stochastic causality is more suited to characterize the experimentally observed complex dynamical processes in large-scale brain networks, rather than the more traditional view of deterministic causality. We strongly support this conclusion and provide two additional examples that may enhance and complement this review: (i) a generalization of the Wiener-Granger Causality (WGC) to fit better the complexity of brain networks; (ii) employment of criticality as a key concept highly relevant to interpreting causality and non-locality in large-scale brain networks.

  6. 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

  7. Measures of Causality in Complex Datasets with Application to Financial Data

    NASA Astrophysics Data System (ADS)

    Zaremba, Anna; Aste, Tomaso

    2014-04-01

    This article investigates the causality structure of financial time series. We concentrate on three main approaches to measuring causality: linear Granger causality, kernel generalisations of Granger causality (based on ridge regression and the Hilbert--Schmidt norm of the cross-covariance operator) and transfer entropy, examining each method and comparing their theoretical properties, with special attention given to the ability to capture nonlinear causality. We also present the theoretical benefits of applying non-symmetrical measures rather than symmetrical measures of dependence. We apply the measures to a range of simulated and real data. The simulated data sets were generated with linear and several types of nonlinear dependence, using bivariate, as well as multivariate settings. An application to real-world financial data highlights the practical difficulties, as well as the potential of the methods. We use two real data sets: (1) U.S. inflation and one-month Libor; (2) S$\\&$P data and exchange rates for the following currencies: AUDJPY, CADJPY, NZDJPY, AUDCHF, CADCHF, NZDCHF. Overall, we reach the conclusion that no single method can be recognised as the best in all circumstances, and each of the methods has its domain of best applicability. We also highlight areas for improvement and future research.

  8. Assessing Dynamic Spectral Causality by Lagged Adaptive Directed Transfer Function and Instantaneous Effect Factor

    PubMed Central

    Xu, Haojie; Lu, Yunfeng; Zhu, Shanan

    2014-01-01

    It is of significance to assess the dynamic spectral causality among physiological signals. Several practical estimators adapted from spectral Granger causality have been exploited to track dynamic causality based on the framework of time-varying multivariate autoregressive (tvMVAR) models. The non-zero covariance of the model’s residuals has been used to describe the instantaneous effect phenomenon in some causality estimators. However, for the situations with Gaussian residuals in some autoregressive models, it is challenging to distinguish the directed instantaneous causality if the sufficient prior information about the “causal ordering” is missing. Here, we propose a new algorithm to assess the time-varying causal ordering of tvMVAR model under the assumption that the signals follow the same acyclic causal ordering for all time lags and to estimate the instantaneous effect factor (IEF) value in order to track the dynamic directed instantaneous connectivity. The time-lagged adaptive directed transfer function (ADTF) is also estimated to assess the lagged causality after removing the instantaneous effect. In the present study, we firstly investigated the performance of the causal-ordering estimation algorithm and the accuracy of IEF value. Then, we presented the results of IEF and time-lagged ADTF method by comparing with the conventional ADTF method through simulations of various propagation models. Statistical analysis results suggest that the new algorithm could accurately estimate the causal ordering and give a good estimation of the IEF values in the Gaussian residual conditions. Meanwhile, the time-lagged ADTF approach is also more accurate in estimating the time-lagged dynamic interactions in a complex nervous system after extracting the instantaneous effect. In addition to the simulation studies, we applied the proposed method to estimate the dynamic spectral causality on real visual evoked potential (VEP) data in a human subject. Its usefulness in

  9. Causality analysis in business performance measurement system using system dynamics methodology

    NASA Astrophysics Data System (ADS)

    Yusof, Zainuridah; Yusoff, Wan Fadzilah Wan; Maarof, Faridah

    2014-07-01

    One of the main components of the Balanced Scorecard (BSC) that differentiates it from any other performance measurement system (PMS) is the Strategy Map with its unidirectional causality feature. Despite its apparent popularity, criticisms on the causality have been rigorously discussed by earlier researchers. In seeking empirical evidence of causality, propositions based on the service profit chain theory were developed and tested using the econometrics analysis, Granger causality test on the 45 data points. However, the insufficiency of well-established causality models was found as only 40% of the causal linkages were supported by the data. Expert knowledge was suggested to be used in the situations of insufficiency of historical data. The Delphi method was selected and conducted in obtaining the consensus of the causality existence among the 15 selected expert persons by utilizing 3 rounds of questionnaires. Study revealed that only 20% of the propositions were not supported. The existences of bidirectional causality which demonstrate significant dynamic environmental complexity through interaction among measures were obtained from both methods. With that, a computer modeling and simulation using System Dynamics (SD) methodology was develop as an experimental platform to identify how policies impacting the business performance in such environments. The reproduction, sensitivity and extreme condition tests were conducted onto developed SD model to ensure their capability in mimic the reality, robustness and validity for causality analysis platform. This study applied a theoretical service management model within the BSC domain to a practical situation using SD methodology where very limited work has been done.

  10. Career Development in Finland.

    ERIC Educational Resources Information Center

    Kurhila, Asta; Onnismaa, Jussi

    Finland has a strong professional guidance and counseling system. Guidance counselors from the labor administration and vocational guidance psychologists are available in the school systems. In the past, particularly strong emphasis was placed on guidance classes within the curriculum. Now, however, the time prescribed for such classes has been…

  11. Sami Education in Finland

    ERIC Educational Resources Information Center

    Keskitalo, Pigga; Maatta, Kaarina; Uusiautti, Satu

    2012-01-01

    The purpose of this article is, first, to describe Sami children's education and its status in the Finnish education system and, secondly, to contemplate its development in Finland. The core of the article is intertwined with issues concerning the status, language, and culture of indigenous peoples. According to the article, the western school…

  12. 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.

  13. Environmental Setting of the Granger Drain and DR2 Basins, Washington, 2003-04

    USGS Publications Warehouse

    Payne, Karen L.; Johnson, Henry M.; Black, Robert W.

    2007-01-01

    The Granger Drain and DR2 basins are located in the Yakima River basin in south central Washington. These agricultural basins are one of five areas in the United States selected for study as part of the National Water-Quality Assessment Program Agricultural Chemicals: Source, Transport, and Fate Study. The Program is designed to describe water-quality conditions and trends based on representative surface- and ground-water resources across the Nation. The objective of the Agricultural Chemicals topical study is to investigate the sources, transport, and fate of selected agricultural chemicals in a variety of agriculturally diverse environmental settings. The Granger Drain and DR2 basins were selected for the Agricultural Chemicals topical study because they represent the irrigated agricultural setting that characterizes eastern Washington. These basins are located in one of the most productive agricultural areas in the United States. This report describes the environmental setting of the Granger Drain and DR2 basins in the context of how agricultural practices, including agricultural chemical applications and irrigation methods, interface with natural settings and hydrologic processes.

  14. Handwashing in Finland.

    PubMed

    Ojajärvi, J

    1991-06-01

    To prevent skin problems we have recommended in Finland that hospital personnel should avoid soap or other detergents for handwashing and instead use alcoholic preparations containing emollients such as 2% glycerol. Alcohol with emollient disinfection is used frequently in hospitals and it causes fewer complaints of skin dryness than washing with soap. However, there are still members of staff who have hand skin problems. Our studies conducted during winter have shown that when these persons used emulsion for hand cleansing, instead of washing with soap, skin deterioration was much less, allowing alcoholic disinfection of the hands whenever necessary, without impairment of the disinfecting effect of alcohol. PMID:1679445

  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. 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

  18. 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…

  19. 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.

  20. Teachers as Leaders in Finland

    ERIC Educational Resources Information Center

    Sahlberg, Pasi

    2013-01-01

    During the last decade, thousands of visitors have flocked to Finland--now a leader in education rankings--to uncover this small Nordic country's secret to its education success. In this article, Finnish educator and scholar Pasi Sahlberg explains how Finland has managed such a feat. A rigorous graduate degree and at least five years of…

  1. The Language Situation in Finland.

    ERIC Educational Resources Information Center

    Latomaa, Sirkku; Nuolijarvi, Pirkko

    2002-01-01

    Provides an overview of the language situation in Finland, an officially bilingual country in Northern Europe. Presents the language profile of Finland, gives a detailed overview of the spread of all the languages used in the country, focuses on language planning and language policy legislation, discusses the current status of languages spoken in…

  2. 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

  3. Finland to Join ESO

    NASA Astrophysics Data System (ADS)

    2004-02-01

    Finland will become the eleventh member state of the European Southern Observatory (ESO) [1]. Today, during a ceremony at the ESO Headquarters in Garching (Germany), a corresponding Agreement was signed by the Finnish Minister of Education and Science, Ms. Tuula Haatainen and the ESO Director General, Dr. Catherine Cesarsky, in the presence of other high officials from Finland and the ESO member states (see Video Clip 02/04 below). Following subsequent ratification by the Finnish Parliament of the ESO Convention and the associated protocols [2], it is foreseen that Finland will formally join ESO on July 1, 2004. Uniting European Astronomy ESO PR Photo 03/04 ESO PR Photo 03/04 Caption : Signing of the Finland-ESO Agreement on February 9, 2004, at the ESO Headquarters in Garching (Germany). At the table, the ESO Director General, Dr. Catherine Cesarsky, and the Finnish Minister of Education and Science, Ms. Tuula Haatainen . [Preview - JPEG: 400 x 499 pix - 52k] [Normal - JPEG: 800 x 997 pix - 720k] [Full Res - JPEG: 2126 x 2649 pix - 2.9M] The Finnish Minister of Education and Science, Ms. Tuula Haatainen, began her speech with these words: "On behalf of Finland, I am happy and proud that we are now joining the European Southern Observatory, one of the most successful megaprojects of European science. ESO is an excellent example of the potential of European cooperation in science, and along with the ALMA project, more and more of global cooperation as well." She also mentioned that besides science ESO offers many technological challenges and opportunities. And she added: "In Finland we will try to promote also technological and industrial cooperation with ESO, and we hope that the ESO side will help us to create good working relations. I am confident that Finland's membership in ESO will be beneficial to both sides." Dr. Catherine Cesarsky, ESO Director General, warmly welcomed the Finnish intention to join ESO. "With the accession of their country to ESO, Finnish

  4. Infrared technology in Finland

    NASA Astrophysics Data System (ADS)

    Hartikainen, Jari A.

    2003-01-01

    This paper presents the main actors in the Finnish infrared research community in the Defense Forces, the civilian research institutes and industry. Within the Defence Forces, the Defence Forces Research Centre (PvTT) has a key role as the most important research institute dealing with military technology in Finland and as an integrator of civilian expertise. The basic research strategy of the Finnish Defense Forces is to rely on external research institutes (either domestic or foreign) and to concentrate its own resources only on the areas where external expertise is not available. Accordingly, the research focus of PvTT is on the signature research and the environmental conditions affecting the performance of infrared sensors. The paper also describes the work done at the Technical Research Centre of Finland (VTT) and at various universities. The role of the Finnish defense industry has been fairly modest, but both its own products and recent technology transfer agreements may change the situation in the long run.

  5. 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…

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Systemic risk and causality dynamics of the world international shipping market

    NASA Astrophysics Data System (ADS)

    Zhang, Xin; Podobnik, Boris; Kenett, Dror Y.; Eugene Stanley, H.

    2014-12-01

    Various studies have reported that many economic systems have been exhibiting an increase in the correlation between different market sectors, a factor that exacerbates the level of systemic risk. We measure this systemic risk of three major world shipping markets, (i) the new ship market, (ii) the second-hand ship market, and (iii) the freight market, as well as the shipping stock market. Based on correlation networks during three time periods, that prior to the financial crisis, during the crisis, and after the crisis, minimal spanning trees (MSTs) and hierarchical trees (HTs) both exhibit complex dynamics, i.e., different market sectors tend to be more closely linked during financial crisis. Brownian distance correlation and Granger causality test both can be used to explore the directional interconnectedness of market sectors, while Brownian distance correlation captures more dependent relationships, which are not observed in the Granger causality test. These two measures can also identify and quantify market regression periods, implying that they contain predictive power for the current crisis.

  11. International report Finland

    SciTech Connect

    Not Available

    1982-04-01

    The Valentin Shashin, the world's first dynamically positioned ice-class drillship for Arctic conditions, has been completed by Rauma-Repola Oy's Mantyluoto Works in Pori, Finland and delivered to V/O Sudoimport, the Soviet Union. This drillship is the first of three such vessels ordered by the Soviet Union in 1979 for oil exploration in Russia's Arctic waters. All three drillships will be capable of operating in water depths to 300 m and of drilling to 20,000 ft in winds of 23 m/sec, in significant wave heights to 4.7 m and currents to 1 m/sec. Since the vessels are to be used in hostile Arctic conditions, the design incorporates a great deal of sophisticated equipment for operating in heavy seas and avoiding hazards, such as icebergs, that may exist in the drilling area. Included is a quick disconnect system that will allow the ship to detach from the drilling mode in approximately three minutes.

  12. 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.

  13. 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

  14. Productivity Analysis of Public and Private Airports: A Causal Investigation

    NASA Technical Reports Server (NTRS)

    Vasigh, Bijan; Gorjidooz, Javad

    2007-01-01

    Around the world, airports are being viewed as enterprises, rather than public services, which are expected to be managed efficiently and provide passengers with courteous customer services. Governments are, increasingly, turning to the private sectors for their efficiency in managing the operation, financing, and development, as well as providing security for airports. Operational and financial performance evaluation has become increasingly important to airport operators due to recent trends in airport privatization. Assessing performance allows the airport operators to plan for human resources and capital investment as efficiently as possible. Productivity measurements may be used as comparisons and guidelines in strategic planning, in the internal analysis of operational efficiency and effectiveness, and in assessing the competitive position of an airport in transportation industry. The primary purpose of this paper is to investigate the operational and financial efficiencies of 22 major airports in the United States and Europe. These airports are divided into three groups based on private ownership (7 British Airport Authority airports), public ownership (8 major United States airports), and a mix of private and public ownership (7 major European Union airports. The detail ownership structures of these airports are presented in Appendix A. Total factor productivity (TFP) model was utilized to measure airport performance in terms of financial and operational efficiencies and to develop a benchmarking tool to identify the areas of strength and weakness. A regression model was then employed to measure the relationship between TFP and ownership structure. Finally a Granger causality test was performed to determine whether ownership structure is a Granger cause of TFP. The results of the analysis presented in this paper demonstrate that there is not a significant relationship between airport TFP and ownership structure. Airport productivity and efficiency is

  15. 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…

  16. 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…

  17. 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

  18. 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…

  19. 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…

  20. 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…

  1. 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…

  2. 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.

  3. Canadian Art Partnership Program in Finland

    ERIC Educational Resources Information Center

    Ketovuori, Mikko

    2011-01-01

    This article is about a multidisciplinary R&D project in which a Canadian Learning Through The Arts (LTTA) program was imported to Finland in 2003-2004. Cultural differences in arts education in Finland and Canada are discussed. While Finland has a national school curriculum with all the arts included. Canada relies more on partnerships to ensure…

  4. 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

  5. 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.…

  6. 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…

  7. 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

  8. Multivariate dynamical systems models for estimating causal interactions in fMRI

    PubMed Central

    Ryali, Srikanth; Supekar, Kaustubh; Chen, Tianwen; Menon, Vinod

    2010-01-01

    Analysis of dynamical interactions between distributed brain areas is of fundamental importance for understanding cognitive information processing. However, estimating dynamic causal interactions between brain regions using functional magnetic resonance imaging (fMRI) poses several unique challenges. For one, fMRI measures Blood Oxygenation Level Dependent (BOLD) signals, rather than the underlying latent neuronal activity. Second, regional variations in the hemodynamic response function (HRF) can significantly influence estimation of casual interactions between them. Third, causal interactions between brain regions can change with experimental context over time. To overcome these problems, we developed a novel state-space Multivariate Dynamical Systems (MDS) model to estimate intrinsic and experimentally-induced modulatory causal interactions between multiple brain regions. A probabilistic graphical framework is then used to estimate the parameters of MDS as applied to fMRI data. We show that MDS accurately takes into account regional variations in the HRF and estimates dynamic causal interactions at the level of latent signals. We develop and compare two estimation procedures using maximum likelihood estimation (MLE) and variational Bayesian (VB) approaches for inferring model parameters. Using extensive computer simulations, we demonstrate that, compared to Granger causal analysis (GCA), MDS exhibits superior performance for a wide range of signal to noise ratios (SNRs), sample length and network size. Our simulations also suggest that GCA fails to uncover causal interactions when there is a conflict between the direction of intrinsic and modulatory influences. Furthermore, we show that MDS estimation using VB methods is more robust and performs significantly better at low SNRs and shorter time series than MDS with MLE. Our study suggests that VB estimation of MDS provides a robust method for estimating and interpreting causal network interactions in fMRI data

  9. Disrupted causal connectivity anchored on the anterior cingulate cortex in first-episode medication-naive major depressive disorder.

    PubMed

    Feng, Zhan; Xu, Shunliang; Huang, Manli; Shi, Yushu; Xiong, Bing; Yang, Hong

    2016-01-01

    In recent years, major depressive disorder (MDD) has been demonstrated to be associated with abnormalities in neural networks, particularly the prefrontal-limbic network (PLN). However, there are few current studies that have examined information flow in the PLN. In this study, Granger causality analysis (GCA), based on signed regression coefficient, was used to explore changes in causal connectivity in resting-state PLNs of MDD patients. A total of 23 first-episode medication-naïve MDD patients and 20 normal control participants were subjected to resting-state functional magnetic resonance imaging (RS-fMRI) scans. Increased causal effects of the right insular cortex, right putamen and right caudate on the rostral anterior cingulate cortex (rACC) and reduced causal effects of bilateral dorsolateral prefrontal cortex (DLPFC) and left orbitofrontal cortex (OFC) on the rACC were found in MDD patients compared to normal controls. The extensive reduction in the causal effect of the prefrontal cortex (PFC) demonstrates impaired top-down cognitive control in MDD patients. Changes in the causal relationship between the right insula and rACC suggest problems in coordination of the default mode network by the right anterior insular cortex (rAI). These findings provide valuable insight into MDD-related neural network disorders reported in previous RS-fMRI studies and may potentially guide clinical treatment of MDD in the future. PMID:26234517

  10. Beta- and gamma-band activity reflect predictive coding in the processing of causal events.

    PubMed

    van Pelt, Stan; Heil, Lieke; Kwisthout, Johan; Ondobaka, Sasha; van Rooij, Iris; Bekkering, Harold

    2016-06-01

    In daily life, complex events are perceived in a causal manner, suggesting that the brain relies on predictive processes to model them. Within predictive coding theory, oscillatory beta-band activity has been linked to top-down predictive signals and gamma-band activity to bottom-up prediction errors. However, neurocognitive evidence for predictive coding outside lower-level sensory areas is scarce. We used magnetoencephalography to investigate neural activity during probability-dependent action perception in three areas pivotal for causal inference, superior temporal sulcus, temporoparietal junction and medial prefrontal cortex, using bowling action animations. Within this network, Granger-causal connectivity in the beta-band was found to be strongest for backward top-down connections and gamma for feed-forward bottom-up connections. Moreover, beta-band power in TPJ increased parametrically with the predictability of the action kinematics-outcome sequences. Conversely, gamma-band power in TPJ and MPFC increased with prediction error. These findings suggest that the brain utilizes predictive-coding-like computations for higher-order cognition such as perception of causal events. PMID:26873806

  11. Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

    NASA Astrophysics Data System (ADS)

    Xu, Chuan-Ming; Yan, Yan; Zhu, Xiao-Wu; Li, Xiao-Teng; Chen, Xiao-Song

    2013-11-01

    The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

    Lozano, A. C.

    2010-12-01

    Attribution of climate change has been predominantly based on simulations using physical climate models. These approaches rely heavily on the employed models and are thus subject to their shortcomings. Given the physical models’ limitations in describing the complex system of climate, we propose an alternative approach to climate change attribution that is data centric in the sense that it relies on actual measurements of climate variables and human and natural forcing factors. We present a novel class of methods to infer causality from spatial-temporal data, as well as a procedure to incorporate extreme value modeling into our methodology in order to address the attribution of extreme climate events. We develop a collection of causal modeling methods using spatio-temporal data that combine graphical modeling techniques with the notion of Granger causality. “Granger causality” is an operational definition of causality from econometrics, which is based on the premise that if a variable causally affects another, then the past values of the former should be helpful in predicting the future values of the latter. In its basic version, our methodology makes use of the spatial relationship between the various data points, but treats each location as being identically distributed and builds a unique causal graph that is common to all locations. A more flexible framework is then proposed that is less restrictive than having a single causal graph common to all locations, while avoiding the brittleness due to data scarcity that might arise if one were to independently learn a different graph for each location. The solution we propose can be viewed as finding a middle ground by partitioning the locations into subsets that share the same causal structures and pooling the observations from all the time series belonging to the same subset in order to learn more robust causal graphs. More precisely, we make use of relationships between locations (e.g. neighboring

  15. 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

  16. 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

  17. 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

  18. Sugihara causality analysis of scalp EEG for detection of early Alzheimer's disease

    PubMed Central

    McBride, Joseph C.; Zhao, Xiaopeng; Munro, Nancy B.; Jicha, Gregory A.; Schmitt, Frederick A.; Kryscio, Richard J.; Smith, Charles D.; Jiang, Yang

    2014-01-01

    Recently, Sugihara proposed an innovative causality concept, which, in contrast to statistical predictability in Granger sense, characterizes underlying deterministic causation of the system. This work exploits Sugihara causality analysis to develop novel EEG biomarkers for discriminating normal aging from mild cognitive impairment (MCI) and early Alzheimer's disease (AD). The hypothesis of this work is that scalp EEG based causality measurements have different distributions for different cognitive groups and hence the causality measurements can be used to distinguish between NC, MCI, and AD participants. The current results are based on 30-channel resting EEG records from 48 age-matched participants (mean age 75.7 years) — 15 normal controls (NCs), 16 MCI, and 17 early-stage AD. First, a reconstruction model is developed for each EEG channel, which predicts the signal in the current channel using data of the other 29 channels. The reconstruction model of the target channel is trained using NC, MCI, or AD records to generate an NC-, MCI-, or AD-specific model, respectively. To avoid over fitting, the training is based on the leave-one-out principle. Sugihara causality between the channels is described by a quality score based on comparison between the reconstructed signal and the original signal. The quality scores are studied for their potential as biomarkers to distinguish between the different cognitive groups. First, the dimension of the quality scores is reduced to two principal components. Then, a three-way classification based on the principal components is conducted. Accuracies of 95.8%, 95.8%, and 97.9% are achieved for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. This work presents a novel application of Sugihara causality analysis to capture characteristic changes in EEG activity due to cognitive deficits. The developed method has excellent potential as individualized biomarkers in the detection of

  19. A causality between fund performance and stock market

    NASA Astrophysics Data System (ADS)

    Kim, Ho-Yong; Kwon, Okyu; Oh, Gabjin

    2016-02-01

    We investigate whether the characteristic fund performance indicators (FPI), such as the fund return, the Net asset value (NAV) and the cash flow, are correlated with the asset price movement using information flows estimated by the Granger causality test. First, we find that the information flow of FPI is most sensitive to extreme events of the Korean stock market, which include negative events such as the sub-prime crisis and the impact of QE (quantitative easing) by the US subprime and Europe financial crisis as well as the positive events of the golden period of Korean Composite Stock Price Index (KOSPI), except for the fund cash flow. Second, both the fund return and the NAV exhibit significant correlations with the KOSPI, whereas the cash flow is not correlated with the stock market. This result suggests that the information resulting from the ability of the fund manager should influence stock market. Finally, during market crisis period, information flows between FPI and the Korean stock market are significantly positively correlated with the market volatility.

  20. 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…

  1. 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.

  2. 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.

  3. 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.

  4. Model-free causality analysis of cardiovascular variability detects the amelioration of autonomic control in Parkinson's disease patients undergoing mechanical stimulation.

    PubMed

    Bassani, Tito; Bari, Vlasta; Marchi, Andrea; Tassin, Stefano; Dalla Vecchia, Laura; Canesi, Margherita; Barbic, Franca; Furlan, Raffaello; Porta, Alberto

    2014-07-01

    We tested the hypothesis that causality analysis, applied to the spontaneous beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP), can identify the improvement of autonomic control linked to plantar mechanical stimulation in patients with Parkinson's disease (PD). A causality index, measuring the strength of the association from SAP to HP variability, and derived according to the Granger paradigm (i.e. SAP causes HP if the inclusion of SAP into the set of signals utilized to describe cardiovascular interactions improves the prediction of HP series), was calculated using both linear model-based (MB) and nonlinear model-free (MF) approaches. Univariate HP and SAP variability indices in time and frequency domains, and bivariate descriptors of the HP-SAP variability interactions were computed as well. We studied ten PD patients (age range: 57-78 years; Hoehn-Yahr scale: 2-3; six males, four females) without orthostatic hypotension or symptoms of orthostatic intolerance and 'on-time' according to their habitual pharmacological treatment. PD patients underwent recordings at rest in a supine position and during a head-up tilt before, and 24 h after, mechanical stimulation was applied to the plantar surface of both feet. The MF causality analysis indicated a greater involvement of baroreflex in regulating HP-SAP variability interactions after mechanical stimulation. Remarkably, MB causality and more traditional univariate or bivariate techniques could not detect changes in cardiovascular regulation after mechanical stimulation, thus stressing the importance of accounting for nonlinear dynamics in PD patients. Due to the higher statistical power of MF causality we suggest its exploitation to monitor the baroreflex control improvement in PD patients, and we encourage the clinical application of the Granger causality approach to evaluate the modification of the autonomic control in relation to the application of a pharmacological treatment, a

  5. 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…

  6. 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…

  7. 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.…

  8. 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…

  9. 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…

  10. 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

  11. 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

  12. 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

  13. Contemporary Issues of Occupational Education in Finland.

    ERIC Educational Resources Information Center

    Lasonen, Johanna, Ed.; Stenstrom, Marja-Leena, Ed.

    This book contains 28 papers about the current status of occupational education in Finland, with special emphasis on context factors, structural and pedagogical reform, and quality management. The following papers are included: "Introduction of Educational Structure in Finland" (Johanna Lasonen, Marja-Leena Stenstrom); "Vocational Education and…

  14. The New Member States: Austria, Finland, Sweden.

    ERIC Educational Resources Information Center

    Goetschy, Janine; And Others

    1995-01-01

    Includes "Difficult Metamorphosis of the Social 'Models' of the Nordic Countries" (Goetschy); "Swedish Training System" (Ottersten); "Features of Vocational Education in Finland" (Kyro); "Boom in Apprenticeship Training in Finland" (Vartiainen); "Vocational Training in Austria" (Riemer); "Reforms in the Vocational Education and Training Systems of…

  15. 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

  16. 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

  17. 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

  18. ["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

  19. Local Activity and Causal Connectivity in Children with Benign Epilepsy with Centrotemporal Spikes.

    PubMed

    Wu, Yun; Ji, Gong-Jun; Zang, Yu-Feng; Liao, Wei; Jin, Zhen; Liu, Ya-Li; Li, Ke; Zeng, Ya-Wei; Fang, Fang

    2015-01-01

    The aim of the current study was to localize the epileptic focus and characterize its causal relation with other brain regions, to understand the cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes (BECTS). Resting-state functional magnetic resonance imaging (fMRI) was performed in 37 children with BECTS and 25 children matched for age, sex and educational achievement. We identified the potential epileptogenic zone (EZ) by comparing the amplitude of low frequency fluctuation (ALFF) of spontaneous blood oxygenation level dependent fMRI signals between the groups. Granger causality analysis was applied to explore the causal effect between EZ and the whole brain. Compared with controls, children with BECTS had significantly increased ALFF in the right postcentral gyrus and bilateral calcarine, and decreased ALFF in the left anterior cingulate cortex, bilateral putaman/caudate, and left cerebellum. ALFF values in the putaman/caudate were positively correlated with verbal IQ scores in patients. The ALFF values in cerebellum and performance IQ scores were negatively correlated in patients. These results suggest that ALFF disturbances in the putaman/caudate and cerebellum play an important role in BECTS cognitive dysfunction. Compared with controls, the patients showed increased driving effect from the EZ to the right medial frontal cortex and posterior cingulate cortex and decreased causal effects from the EZ to left inferior frontal gyrus. The causal effect of the left inferior frontal gyrus negatively correlated with disease duration, which suggests a relation between the epileptiform activity and language impairment. All together, these findings provide additional insight into the neurophysiological mechanisms of epilepitogenisis and cognitive dysfunction associated with BECTS. PMID:26225427

  20. Local Activity and Causal Connectivity in Children with Benign Epilepsy with Centrotemporal Spikes

    PubMed Central

    Zang, Yu-Feng; Liao, Wei; Jin, Zhen; Liu, Ya-Li; Li, Ke; Zeng, Ya-Wei; Fang, Fang

    2015-01-01

    The aim of the current study was to localize the epileptic focus and characterize its causal relation with other brain regions, to understand the cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes (BECTS). Resting-state functional magnetic resonance imaging (fMRI) was performed in 37 children with BECTS and 25 children matched for age, sex and educational achievement. We identified the potential epileptogenic zone (EZ) by comparing the amplitude of low frequency fluctuation (ALFF) of spontaneous blood oxygenation level dependent fMRI signals between the groups. Granger causality analysis was applied to explore the causal effect between EZ and the whole brain. Compared with controls, children with BECTS had significantly increased ALFF in the right postcentral gyrus and bilateral calcarine, and decreased ALFF in the left anterior cingulate cortex, bilateral putaman/caudate, and left cerebellum. ALFF values in the putaman/caudate were positively correlated with verbal IQ scores in patients. The ALFF values in cerebellum and performance IQ scores were negatively correlated in patients. These results suggest that ALFF disturbances in the putaman/caudate and cerebellum play an important role in BECTS cognitive dysfunction. Compared with controls, the patients showed increased driving effect from the EZ to the right medial frontal cortex and posterior cingulate cortex and decreased causal effects from the EZ to left inferior frontal gyrus. The causal effect of the left inferior frontal gyrus negatively correlated with disease duration, which suggests a relation between the epileptiform activity and language impairment. All together, these findings provide additional insight into the neurophysiological mechanisms of epilepitogenisis and cognitive dysfunction associated with BECTS. PMID:26225427

  1. 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

  2. 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

  3. Population and policy in Finland.

    PubMed

    Hulkko, J

    1989-03-01

    Finland, with a population of 4.9 million, currently has an overall fertility rate of 1.6. There is a small population growth, but this is due to a large reproductive age group, return migration of Finns from Sweden, and a decrease in mortality that has increased the proportion of old people in the population. The state has no official population policy. A recommendation of the Finnish Committee on the World Population Year 1974 that the government establish an agency for population policy has not been adopted. The coalition government now in power has a program, however, aimed at influencing population growth. The program includes proposals to reduce work hours for parents with small children, increase the age limit for participation in the child allowance system, and increase the number of municipal day care facilities. Concerning regional policy, the government wants a balanced development of the country's different regions. Subsidiary industries of agriculture and forestry are being encouraged to preserve population levels in sparse areas. Finland also supports a health policy emphasizing preventive and non-institutional aspects of health care, with targets of life expectancy set at 82 years for women and 75 years for men by the year 2000. PMID:12222205

  4. On the causal links between health indicator, output, combustible renewables and waste consumption, rail transport, and CO2 emissions: the case of Tunisia.

    PubMed

    Ben Jebli, Mehdi

    2016-08-01

    This study employs the autoregressive distributed lag (ARDL) approach and Granger causality test to investigate the short- and long-run relationships between health indicator, real GDP, combustible renewables and waste consumption, rail transport, and carbon dioxide (CO2) emissions for the case of Tunisia, spanning the period of 1990-2011. The empirical findings suggest that the Fisher statistic of the Wald test confirm the existence of a long-run relationship between the variables. Moreover, the long-run estimated elasticities of the ARDL model provide that output and combustible renewables and waste consumption have a positive and statistically significant impact on health situation, while CO2 emissions and rail transport both contribute to the decrease of health indicator. Granger causality results affirm that, in the short-run, there is a unidirectional causality running from real GDP to health, a unidirectional causality from health to combustible renewables and waste consumption, and a unidirectional causality from all variables to CO2 emissions. In the long-run, all the computed error correction terms are significant and confirm the existence of long-run association among the variables. Our recommendations for the Tunisian policymakers are as follows: (i) exploiting wastes and renewable fuels can be a good strategy to eliminate pollution caused by emissions and subsequently improve health quality, (ii) the use of renewable energy as a main source for national rail transport is an effective strategy for public health, (iii) renewable energy investment projects are beneficial plans for the country as this contributes to the growth of its own economy and reduce energy dependence, and (iii) more renewable energy consumption leads not only to decrease pollution but also to stimulate health situation because of the increase of doctors and nurses numbers. PMID:27180840

  5. 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)

  6. New records of the genus Iporhogas Granger (Hymenoptera, Braconidae, Rogadinae) from Vietnam, with description of four new species

    PubMed Central

    Long, Khuat Dang

    2014-01-01

    Abstract The genus Iporhogas Granger, 1949 (Braconidae: Rogadinae) is recorded for the first time for Vietnam. Four new species of the genus Iporhogas, viz. Iporhogas albilateralis sp. n., I. contrastus sp. n., I. simulatus sp. n. and I. tricoloratus sp. n., from Vietnam are described and illustrated, and additionally, one species, Iporhogas guangxiensis Chen & He, 1997, is newly recorded for Vietnam’s fauna of the family Braconidae. A key to the five Vietnamese species of the genus Iporhogas and a checklist with distributions of the ten species are provided. PMID:25161368

  7. 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.

  8. 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.

  9. The Secret to Finland's Success: Educating Teachers. Research Brief

    ERIC Educational Resources Information Center

    Sahlberg, Pasi

    2010-01-01

    In the last decade, Finland has emerged as the leading OECD country in educational achievement. In examining the sources of Finland's dramatic rise to the top, research shows one key element that has impacted Finland's success above all others: excellent teachers. This policy brief details the key elements of Finland's successful system, examining…

  10. 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

  11. ESO Welcomes Finland as Eleventh Member State

    NASA Astrophysics Data System (ADS)

    Cesarsky, C.

    2004-09-01

    In early July, Finland joined ESO as the eleventh member state, following the completion of the formal accession procedure. Before this event, however, Finland and ESO had been in contact for a long time. Under an agreement with Sweden, Finnish astronomers had for quite a while enjoyed access to the SEST at La Silla. Finland had also been a very active participant in ESO's educational activities since they began in 1993. It became clear, that science and technology, as well as education, were priority areas for the Finnish government.

  12. 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…

  13. University Mergers in Finland: Mediating Global Competition

    ERIC Educational Resources Information Center

    Välimaa, Jussi; Aittola, Helena; Ursin, Jani

    2014-01-01

    University mergers have become a common strategy for increasing global competitiveness. In this chapter, the authors analyze the implementation of mergers in Finnish universities from the perspective of social justice as conceived within Finland and other Nordic countries.

  14. Checklist of the Cecidomyiidae (Diptera) of Finland

    PubMed Central

    Jaschhof, Mathias; Skuhravá, Marcela; Penttinen, Jouni

    2014-01-01

    Abstract A list of the 356 species of Cecidomyiidae (Diptera) recorded from Finland is presented, which comprises 6 Lestremiinae, 156 Micromyinae, 16 Winnertziinae, 69 Porricondylinae, and 109 Cecidomyiinae. The faunistic knowledge of Finnish Winnertziinae, Porricondylinae and Cecidomyiinae is regarded as particularly poor. Based on species numbers known from other countries in Europe, a conservative estimate is 700–800 species of Cecidomyiidae actually occurring in Finland. PMID:25337012

  15. 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

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. The salience network causally influences default mode network activity during moral reasoning

    PubMed Central

    Wilson, Stephen M.; D’Esposito, Mark; Kayser, Andrew S.; Grossman, Scott N.; Poorzand, Pardis; Seeley, William W.; Miller, Bruce L.; Rankin, Katherine P.

    2013-01-01

    Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in

  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. 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

  3. Occupational eye injuries in Finland.

    PubMed

    Saari, K M; Parvi, V

    1984-01-01

    In Finland 11.9% of all industrial accidents in 1973 were eye injuries including superficial eye injuries (79.2%), ultraviolet burns of the cornea (3.9%), eye burns (3.6%), blunt ocular trauma (2,5%), wounds (2.4%), and post-traumatic infections (5.8%). Eye injuries constituted 34.3% of all industrial accidents which needed only ambulatory treatment and 17.5% of all industrial accidents causing an absence for 1-2 days. In 1981 2.1% of all compensated industrial accidents (incapacity for work 3 days or more) were eye injuries. Most compensated eye injuries occurred in manufacturing and in construction work (80.4%) and 8.5% occurred in agriculture. The annual incidence rates of compensated accidents to the eyes (accidents X 1 000/number of employees) were highest in several branches of metal industry (4.96-6.88), excavating and foundation work (6.88), and in logging (5.64). Compensated eye injuries were caused by machines (32.8%), hand tools (25.6%), other equipment and constructions (4.8%), work environment (23.6%), chemical substances (10.8%), and other accidents (2.3%). PMID:6328849

  4. Synanthropic Trichinella infection in Finland.

    PubMed

    Oivanen, Leena; Oksanen, Antti

    2009-02-23

    The first three human trichinellosis cases in Finland were recorded around 1890, and altogether eight cases were registered until 2008. The first infected Finnish swine was found in 1954. From the early 1980s, an increasing trend in the number of infected swine was seen, with the highest number registered in 1996, after which a decrease has been observed. Infected pigs were found yearly until 2004. Since 1954, all slaughtered pigs have been tested for Trichinella, regardless of subsequent export or domestic consumption purpose. All Trichinella infections revealed in pigs are, since 1998, analysed for species by multiplex PCR. So far, all larvae from pig infections have been identified as Trichinella spiralis. During the recent decreasing trend in prevalence, the number of pig farms has also decreased, while the yearly number of slaughtered pigs has remained stable or even slightly increased. For many decades, the Trichinella prevalence in Finnish wildlife has remained high. Foxes, raccoon dogs, wolves, and lynx in the southern part of the country exhibit prevalence exceeding 50%. The most common species in wildlife is Trichinella nativa, a species with very low infectivity to swine, but also, T. spiralis, Trichinella britovi, and Trichinella pseudospiralis occur in wildlife. PMID:19054618

  5. 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.…

  6. 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…

  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. Vibration exposure and prevention in Finland.

    PubMed

    Starck, J; Pyykkö, I; Koskimies, K; Pekkarinen, J

    1994-05-01

    The number of annually compensated occupational diseases due to exposure to hand-arm vibration (HAV) has decreased during the last 15 years. The number of exposed workers has been declining in Finland, especially in forestry work, as harvesters have increasingly replaced manual chain saw operations. During the entire 1970s, forest work caused more cases of vibration-induced occupational diseases than all industrial branches together. The decrease is mainly due to the technical development of chain saws, but also to the effective health care services in Finland. Other factors such as warm transport, warm rest cabins in which to take pauses at work, warm meals, adequate protective clothing, and vocationally adjusted early medical rehabilitation have helped to cut down health hazards, especially in forest work. The number of new cases has been decreasing in Finland not only in forestry but also in other industries. In Finland a considerable amount of research has been conducted to hand-arm vibration, resulting in the increased awareness of the health risks related to certain occupations. This has helped to carry out the Primary Health Care Act (1972) followed by the Occupational Health Care Act (1979) which obligates employers to arrange occupational health care for their employees. We believe that the research activity has contributed significantly to achieving the present health in Finnish work places. The purpose of the present paper is to describe the cases of occupational exposure to HAV, and the effectiveness of different preventive measures in Finland. PMID:7708103

  10. Carbon dioxide emissions, GDP, energy use, and population growth: a multivariate and causality analysis for Ghana, 1971-2013.

    PubMed

    Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

    2016-07-01

    In this study, the relationship between carbon dioxide emissions, GDP, energy use, and population growth in Ghana was investigated from 1971 to 2013 by comparing the vector error correction model (VECM) and the autoregressive distributed lag (ARDL). Prior to testing for Granger causality based on VECM, the study tested for unit roots, Johansen's multivariate co-integration and performed a variance decomposition analysis using Cholesky's technique. Evidence from the variance decomposition shows that 21 % of future shocks in carbon dioxide emissions are due to fluctuations in energy use, 8 % of future shocks are due to fluctuations in GDP, and 6 % of future shocks are due to fluctuations in population. There was evidence of bidirectional causality running from energy use to GDP and a unidirectional causality running from carbon dioxide emissions to energy use, carbon dioxide emissions to GDP, carbon dioxide emissions to population, and population to energy use. Evidence from the long-run elasticities shows that a 1 % increase in population in Ghana will increase carbon dioxide emissions by 1.72 %. There was evidence of short-run equilibrium relationship running from energy use to carbon dioxide emissions and GDP to carbon dioxide emissions. As a policy implication, the addition of renewable energy and clean energy technologies into Ghana's energy mix can help mitigate climate change and its impact in the future. PMID:27030236

  11. [Marriage trends in Finland and Hungary].

    PubMed

    Csernak, J

    1993-10-01

    "The study compares marriage trends of Finland and Hungary, using marriage tables of Finnish males and females born between 1939 and 1965 as well as those of Hungarian males and females born between 1939 and 1968." A major change in marriage behavior in Finland during the 1960s is attributed to changing social and economic conditions, particularly migration to the major cities. "Due to the changes a new marriage pattern is being shaped in Finland's population which is typical of postindustrial societies. In the youngest cohorts of Finnish females the average age at first marriage is likely to exceed 26 years, and at least 25 per cent of them remain ultimately unmarried. In the younger Hungarian cohorts significant decrease in first marriages can similarly be pointed out." (SUMMARY IN ENG AND RUS) PMID:12344978

  12. Finland Becomes Eleventh ESO Member State

    NASA Astrophysics Data System (ADS)

    2004-07-01

    Finland has become the eleventh member state of the European Southern Observatory (ESO) [1]. The formal accession procedure was carried through as planned and has now been completed. Following the signing of the corresponding Agreement earlier this year (ESO PR 02/04), acceptance by the Finnish Parliament and ratification by the Finnish President of the Agreement as well as the ESO Convention and the associated protocols in June [2] and the deposit of the instruments of accession today, Finland has now officially joined ESO. ESO warmly welcomes the new member country and its scientific community that is renowned for their expertise in many frontline areas. The related opportunities will contribute to strenghtening of pioneering research with the powerful facilities at ESO's observatories, to the benefit of Astronomy and Astrophysics as well as European science in general. ESO also looks forward to collaboration with the Finnish high-tech industry. For Finland, the membership in ESO is motivated by scientific and technological objectives as well as by the objective of improving the public understanding of science. The Finnish Government is committed to increasing the public research funding in order to improve the quality, impact and internationalisation of research. Membership in ESO offers unique facilities for astronomical research which would not otherwise be available for Finnish astronomers. Finland is also very interested in taking part in technological development projects in fields like ICT, optics and instrumentation. For young scientists and engineers, ESO is a challenging, international working and learning environment. Finland has already taken part in the educational programmes of ESO, and as a member this activity will be broadened and intensified. In Finland there are also several science journalists and a large community of amateur astronomers who will be very happy to take part in ESO's outreach activities.

  13. Inference of directed climate networks: role of instability of causality estimation methods

    NASA Astrophysics Data System (ADS)

    Hlinka, Jaroslav; Hartman, David; Vejmelka, Martin; Paluš, Milan

    2013-04-01

    Climate data are increasingly analyzed by complex network analysis methods, including graph-theoretical approaches [1]. For such analysis, links between localized nodes of climate network are typically quantified by some statistical measures of dependence (connectivity) between measured variables of interest. To obtain information on the directionality of the interactions in the networks, a wide range of methods exists. These can be broadly divided into linear and nonlinear methods, with some of the latter having the theoretical advantage of being model-free, and principally a generalization of the former [2]. However, as a trade-off, this generality comes together with lower accuracy - in particular if the system was close to linear. In an overall stationary system, this may potentially lead to higher variability in the nonlinear network estimates. Therefore, with the same control of false alarms, this may lead to lower sensitivity for detection of real changes in the network structure. These problems are discussed on the example of daily SAT and SLP data from the NCEP/NCAR reanalysis dataset. We first reduce the dimensionality of data using PCA with VARIMAX rotation to detect several dozens of components that together explain most of the data variability. We further construct directed climate networks applying a selection of most widely used methods - variants of linear Granger causality and conditional mutual information. Finally, we assess the stability of the detected directed climate networks by computing them in sliding time windows. To understand the origin of the observed instabilities and their range, we also apply the same procedure to two types of surrogate data: either with non-stationarity in network structure removed, or imposed in a controlled way. In general, the linear methods show stable results in terms of overall similarity of directed climate networks inferred. For instance, for different decades of SAT data, the Spearman correlation of edge

  14. 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

  15. 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…

  16. 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…

  17. 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.…

  18. 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…

  19. Update on women in physics in Finland

    NASA Astrophysics Data System (ADS)

    Miikkulainen, Kukka; Vapaavuori, Jaana

    2015-12-01

    Despite Finland's role as a forerunner in many areas of gender equality, in the field of physics, the advancement of females to reach the full gender equality has been stagnated for the past decade, and no significant improvements since 2011 can be reported. However, a few interesting PhD theses have focused on gaining a better understanding of the phenomena, and a few seminars on the topic have been organized. However, good, systematically collected statistics on the numbers and salaries of female researches in Finland are still lacking.

  20. Sharable EHR systems in Finland.

    PubMed

    Harno, Kari; Ruotsalainen, Pekka

    2006-01-01

    In Finland, the shared record is a virtual electronic health record (EHR). It consists of health data generated, maintained and preserved by different health care service providers. Two different kinds of technologies for integrating regional EHR-systems are applied, but mainly by using a common middleware. Services provided by this middleware are EHR location services using a link repository and combining EHR-viewing services with security management services including consent management and identification services for health professionals. The Regional Health Information Organization (UUMA) approach is based on a stepwise implementation of integrated regional healthcare services to create a virtually borderless healthcare organization--a patient centered virtual workspace. In the virtual workspace multi-professional teams and patients collaborate and share information regardless of time and place. Presently the regional health information network (RHIN) is comprised of three integrated services between primary, secondary and tertiary care within the county of Uusimaa. The regional healthcare modules consist of an (1) eReferral network, (2) integrated EHR service between health care professionals and (3) PACS system. The eReferral between primary and secondary care not only speeds up the transfer, but also offers an option for communication in the form of eConsultation between general practitioners and hospital specialists. By sharing information and knowledge remote eConsultations create a new working environment for integrated delivery of eServices between the health care providers. Over 100,000 eReferral messages (40 %) were transferred between health care providers. Interactive eConsultations enable supervised care leading to the reduction of outpatient visits and more timely appointments. One third (10/31) of the municipal health centers are connected to the clinics in the Helsinki University Central Hospital by the eReferral system. The link directory

  1. Social capital and health of older Europeans: causal pathways and health inequalities.

    PubMed

    Sirven, Nicolas; Debrand, Thierry

    2012-10-01

    This study uses a time-based approach to examine the causal relationship (Granger-like) between health and social capital for older people in Europe. We use panel data from waves 1 and 2 of SHARE (the Survey of Health, Ageing, and Retirement in Europe) for the analysis. Additional wave 3 data on retrospective life histories (SHARELIFE) are used to model the initial conditions in the model. For each of the first 2 waves, a dummy variable for involvement in social activities (voluntary associations, church, social clubs, etc.) is used as a proxy for social capital as involvement in Putnamesque associations; and seven health dichotomous variables are retained, covering a wide range of physical and mental health measures. A bivariate recursive Probit model is used to simultaneously investigate (i) the influence of baseline social capital on current health - controlling for baseline health and other current covariates, and (ii) the impact of baseline health on current participation in social activities - controlling for baseline social capital and other current covariates. As expected, we account for a reversed causal effect: individual social capital has a causal beneficial impact on health and vice-versa. However, the effect of health on social capital appears to be significantly higher than the social capital effect on health. These results indicate that the sub-population reaching 50 years old in good health has a higher propensity to take part in social activities and to benefit from it. Conversely, the other part of the population in poor health at 50, may see their health worsening faster because of the missing beneficial effect of social capital. Social capital may therefore be a potential vector of health inequalities for the older population. PMID:22748478

  2. Oral health in Finland and the Soviet Union. A joint study.

    PubMed

    Nyyssönen, V; Paunio, I; Borovsky, J

    1984-01-01

    To develop the functions of a health care system it is essential to compare and evaluate the systems of different countries. The World Health Organization (WHO) has emphasized the importance of collaborative studies in the field of epidemiology. In countries with similar social systems the basis for health care is usually the same. Comparison of health care in such countries is relatively easy because in most cases the criteria for functions, diagnosis, etc. are similar. Comparison of countries having different bases for health care and different philosophies of research is much more complicated and time-consuming. Soviet health care, including oral health care, is based on community responsibility and has complex prophylaxis as its main emphasis. In the USSR there are no private dentists. All dental services are available at polyclinics located either near the place of residence or at the work place. In Finland there are two separate systems for oral health care. Children up to the age of 18 and some special groups of the adult population (pregnant women, military recruits, and students) are treated in municipal polyclinics (called health centres in Finland). Otherwise, the adult population is treated mainly by private dentists. The study will be carried out in three towns in Finland and six towns in the USSR. The aim of this study is to describe the causal epidemiology of dental caries among children 6 to 7, 9 and 12 years old in Finland and the Soviet Union. In addition, certain measures and compounds for caries prevention will be tested during 3 years of follow-up.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:6523092

  3. 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…

  4. 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.

  5. 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

  6. The Professional Educator: Lessons from Finland

    ERIC Educational Resources Information Center

    Sahlberg, Pasi

    2011-01-01

    Since Finland emerged in 2000 as the top-scoring Organisation for Economic Co-operation and Development (OECD) nation on the Programme for International Student Assessment (PISA), researchers have been pouring into the country to study the so-called "Finnish miracle." How did a country with an undistinguished education system in the 1980s surge to…

  7. Deep drilling for geothermal energy in Finland

    NASA Astrophysics Data System (ADS)

    Kukkonen, Ilmo

    2016-04-01

    There is a societal request to find renewable CO2-free energy resources. One of the biggest such resources is provided by geothermal energy. In addition to shallow ground heat already extensively used in Finland, deep geothermal energy provides an alternative so far not exploited. Temperatures are high at depth, but the challenge is, how to mine the heat? In this presentation, the geological and geophysical conditions for deep geothermal energy production in Finland are discussed as well as challenges for drilling and conditions at depth for geothermal energy production. Finland is located on ancient bedrock with much lower temperatures than geologically younger volcanically and tectonically active areas. In order to reach sufficiently high temperatures drilling to depths of several kilometres are needed. Further, mining of the heat with, e.g., the principle of Enhanced Geothermal System (EGS) requires high hydraulic conductivity for efficient circulation of fluid in natural or artificial fractures of the rock. There are many issues that must be solved and/or improved: Drilling technology, the EGS concept, rock stress and hydraulic fracturing, scale formation, induced seismicity and ground movements, possible microbial activity, etc. An industry-funded pilot project currently in progress in southern Finland is shortly introduced.

  8. Finland--Internationalism behind a Language Barrier.

    ERIC Educational Resources Information Center

    Kauranne, Jouko

    1991-01-01

    Argues that (1) English should be a compulsory foreign language in Finnish schools; (2) options to teach subjects in foreign languages should be expanded; and (3) the variety of foreign language choices in rural areas of Finland should be enlarged. (SK)

  9. Mathematics Lessons from Finland and Sweden

    ERIC Educational Resources Information Center

    Seaberg, Rebecca L.

    2015-01-01

    In many ways, mathematics classrooms in Finland and Sweden are very similar to what would be considered traditional classrooms in the United States. Classes begin with checking homework and questions, followed by the teacher giving instruction in the new material, and end with students working on their new assignment. There are also interesting…

  10. School-Parent Relations in Finland

    ERIC Educational Resources Information Center

    Risku, Mika; Bjork, Lars G.; Browne-Ferrigno, Tricia

    2012-01-01

    This article provides insight into the nature and scope of home-school cooperation in Finland. Situating the study is a brief overview of the Finnish education system and a discussion of the Programme for International Student Assessment reports that place Finnish student outcomes at the top of rankings among industrialized nations for the past…

  11. From Finland to Kyrgyzstan: A Changing Landscape

    ERIC Educational Resources Information Center

    Schleicher, Andreas K. R.

    2009-01-01

    In the most recent Programme for International Student Assessment of science learning, the equivalent of six school years separate the achievement of 15-year-olds in Finland, the best-performing country, from their counterparts in Kyrgyzstan, a former Soviet republic. Still more than a school year lies between the neighboring countries Canada,…

  12. How Finland Serves Gifted and Talented Pupils

    ERIC Educational Resources Information Center

    Tirri, Kirsi; Kuusisto, Elina

    2013-01-01

    The purpose of this article is to provide an overview of the ways gifted and talented pupils are served in Finland. The trend toward individualism and freedom of choice as well as national policy affecting gifted education are discussed. Empirical research on Finnish teachers' attitudes toward gifted education with respect to the national…

  13. Equality and Cooperation: Finland's Path to Excellence

    ERIC Educational Resources Information Center

    Sarjala, Jukka

    2013-01-01

    For the past decade, Finland has been lauded for consistently being a top performer on international assessments of student achievement. Having spent 25 years in the Ministry of Education, and then another 8 as director general of the National Board of Education, the author was heartened by these accomplishment--but he is also concerned about how…

  14. 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

  15. 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.

  16. 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.

  17. [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

  18. 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.

  19. 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

  20. 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

  1. Air tightness of buildings in Finland

    NASA Astrophysics Data System (ADS)

    Kauppinen, Timo T.

    2001-03-01

    There are no requirements of building air tightness in Finland. Buildings always have thermal bridges and air leak routes, whose impact in decreasing comfort depends on the structures and the way of constructing. Uncontrolled air leaks are cooling the structures and causing draft and, in the long run, defects. These air leaks and thermal bridges can be found only by thermal scanning. In Finland building air tightness has been measured for over 20 years. The procedure includes two stages, in which the target is scanned by a thermal imager. The paper is based on the results of over 200 tests of one-family and detached houses. The air tightness level has improved, but there are still problems in the structural details. The monitoring procedure for therm scanning of buildings should be further developed (there is no generally accepted practice at the moment), as well as air tightness requirements should be created.

  2. Leucocytozoonosis and trypanosomiasis in redstarts in Finland.

    PubMed

    Rintamäki, P T; Huhta, E; Jokimäki, J; Squires-Parsons, D

    1999-07-01

    Leucocytozoon spp. and Trypanosoma spp. blood parasites in the redstart (Phoenicurus phoenicurus) were studied during spring migration 1994 in southern Finland (53 individuals) and the breeding season 1992-1994 in northern Finland (69). Parasite prevalence was higher during the breeding season (48%) than during the migration period (13%), with no age or sex differences in the breeding site birds. In both periods, redstarts were infected by the same blood parasites Leucocytozoon shaartusicum (46% prevalence at the breeding site and 71% during the migration period) and Trypanosoma avium, complex (58% and 43%, respectively). One individual at the breeding site had contracted L. dubreuili and one at the stop-over site had T. everetti. Our results may support the assumption that tissue-hidden parasites relapse during the breeding season when birds may have diminished immune response related to egg production and brood rearing. Another explanation could be that the high abundance of ornithophilic vectors enhance parasite transmission during breeding season in northern Finland. PMID:10479101

  3. Sylvatic Trichinella spp. infection in Finland.

    PubMed

    Airas, Niina; Saari, Seppo; Mikkonen, Taina; Virtala, Anna-Maija; Pellikka, Jani; Oksanen, Antti; Isomursu, Marja; Kilpelä, Seija-Sisko; Lim, Chae W; Sukura, Antti

    2010-02-01

    Although human infections caused by Trichinella sp. have not been reported in Finland for several decades and Trichinella sp. infection in pork has become virtually extinct in the last decade, sylvatic Trichinella spp. infection is still highly prevalent in Finland. Muscle digestion of 2,483 carnivorous wild animals from 9 host species during 1999-2005 showed 617 positive animals (24.8%). Molecular identification from 328 larval isolates revealed 4 different endemic Trichinella species, i.e., T. nativa, T. spiralis, T. britovi, and T. pseudospiralis. Seven percent of the infected animals carried mixed infections. Trichinella nativa was the most common species (74%), but T. spiralis was identified in 12%, T. britovi in 6%, and T. pseudospiralis in 1% of the animals. Host species showed different sample prevalence and Trichinella species distribution. Geographical distribution also varied, with the southern part of the country having significantly higher percentages than the northern part. Infection density was dependent on both the infecting Trichinella species and the host species. Trichinella spiralis was discovered in areas with no known domestic infection cases, indicating that it can also occur in the sylvatic cycle. Raccoon dogs and red foxes are the most important reservoir animals for T. spiralis , as well as for the sylvatic Trichinella species in Finland. PMID:19731970

  4. 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.

  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. 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…

  8. Influence of early life stress on intra- and extra-amygdaloid causal connectivity.

    PubMed

    Grant, Merida M; Wood, Kimberly; Sreenivasan, Karthik; Wheelock, Muriah; White, David; Thomas, Jasmyne; Knight, David C; Deshpande, Gopikrishna

    2015-06-01

    Animal models of early life stress (ELS) are characterized by augmented amygdala response to threat and altered amygdala-dependent behaviors. These models indicate the amygdala is a heterogeneous structure with well-differentiated subnuclei. The most well characterized of these being basolateral (BLA) and central nucleus (CeA). Parallel human imaging findings relative to ELS also reveal enhanced amygdala reactivity and disrupted connectivity but the influence of ELS on amygdala subregion connectivity and modulation of emotion is unclear. Here we employed cytoarchitectonic probability maps of amygdala subregions and Granger causality methods to evaluate task-based intra-amygdaloid and extra-amygdaloid connectivity with the network underlying implicit regulation of emotion in response to unconditioned auditory threat in healthy controls with ELS (N=20) and without a history of ELS (N=14). Groups were determined by response to the Childhood Trauma Questionnaire and threat response determined by unpleasantness ratings. Non-ELS demonstrated narrowly defined BLA-driven intra-amygdaloid paths and concise orbitofrontal cortex (OFC)-CeA-driven extra-amygdaloid connectivity. In contrast, ELS was associated with extensive and robust CeA-facilitated intra- and extra-amygdaloid paths. Non-ELS findings paralleled the known anatomical organization and functional relationships for both intra- and extra-amygdaloid connectivity, while ELS demonstrated atypical intra- and extra-amygdaloid CeA-dominant paths with compensatory modulation of emotion. Specifically, negative causal paths from OFC/BA32 to BLA predicted decreased threat response among non-ELS, while a unique within-amygdala path predicted modulation of threat among ELS. These findings are consistent with compensatory mechanisms of emotion regulation following ELS among resilient persons originating both within the amygdala complex as well as subsequent extra-amygdaloid communication. PMID:25630572

  9. Influence of Early Life Stress on Intra- and Extra-Amygdaloid Causal Connectivity

    PubMed Central

    Grant, Merida M; Wood, Kimberly; Sreenivasan, Karthik; Wheelock, Muriah; White, David; Thomas, Jasmyne; Knight, David C; Deshpande, Gopikrishna

    2015-01-01

    Animal models of early life stress (ELS) are characterized by augmented amygdala response to threat and altered amygdala-dependent behaviors. These models indicate the amygdala is a heterogeneous structure with well-differentiated subnuclei. The most well characterized of these being basolateral (BLA) and central nucleus (CeA). Parallel human imaging findings relative to ELS also reveal enhanced amygdala reactivity and disrupted connectivity but the influence of ELS on amygdala subregion connectivity and modulation of emotion is unclear. Here we employed cytoarchitectonic probability maps of amygdala subregions and Granger causality methods to evaluate task-based intra-amygdaloid and extra-amygdaloid connectivity with the network underlying implicit regulation of emotion in response to unconditioned auditory threat in healthy controls with ELS (N=20) and without a history of ELS (N=14). Groups were determined by response to the Childhood Trauma Questionnaire and threat response determined by unpleasantness ratings. Non-ELS demonstrated narrowly defined BLA-driven intra-amygdaloid paths and concise orbitofrontal cortex (OFC)–CeA-driven extra-amygdaloid connectivity. In contrast, ELS was associated with extensive and robust CeA-facilitated intra- and extra-amygdaloid paths. Non-ELS findings paralleled the known anatomical organization and functional relationships for both intra- and extra-amygdaloid connectivity, while ELS demonstrated atypical intra- and extra-amygdaloid CeA-dominant paths with compensatory modulation of emotion. Specifically, negative causal paths from OFC/BA32 to BLA predicted decreased threat response among non-ELS, while a unique within-amygdala path predicted modulation of threat among ELS. These findings are consistent with compensatory mechanisms of emotion regulation following ELS among resilient persons originating both within the amygdala complex as well as subsequent extra-amygdaloid communication. PMID:25630572

  10. Volatile organic compound sources for Southern Finland

    NASA Astrophysics Data System (ADS)

    Patokoski, Johanna; Ruuskanen, Taina M.; Kajos, Maija K.; Taipale, Risto; Rantala, Pekka; Aalto, Juho; Ryyppö, Timo; Hakola, Hannele; Rinne, Janne

    2014-05-01

    Volatile organic compounds (VOCs) have several sources, both biogenic and anthropogenic. Emissions of biogenic VOCs in a global scale are estimated to be an order of magnitude higher than anthropogenic ones. However, in densely populated areas and during winter time the anthropogenic VOC emissions dominate over the biogenic ones. The aim of this study was to clarify potential local sources and source areas of VOCs in different seasons. Diurnal behaviour in winter and spring were also compared at two different sites in Finland: SMEAR II and III (Station for Measuring Ecosystem - Atmosphere Relations). SMEAR II is a rural site located in Hyytiälä in Southern Finland 220 km North-West from Helsinki whereas SMEAR III is background urban site located 5 km from the downtown of Helsinki. The volume mixing ratios of VOCs were measured with a proton-transfer-reaction mass spectrometer (PTR-MS, Ionicon Analytik GmbH, Austria) during years 2006-2011. Other trace gases such as CO, NOXand SO2 were also measured in both sites and used for source analysis. Source areas for long term VOC measurements were investigated with trajectory analysis and sources for local and regional concentrations were determined by Unmix multivariate receptor model. Forest fires affect air quality and the biggest smoke plumes can be seen in satellite images and even hinder visibility in the plume areas. They provide temporally and spatially well-defined sources that can be used to verify source area estimates. During the measurement periods two different forest fire episodes with several hotspots, happened in Russia. Forest fires which showed up in these measurements were in 2006 near the border of Finland in Vyborg area and 2010 in Moscow area. Forest fire episodes were clearly observed in trajectory analysis for benzene, toluene and methanol and also CO and NOX. In addition to event sources continuous source areas were determined. Anthropogenic local sources seemed to be dominant during winter in

  11. 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…

  12. 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…

  13. 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.

  14. 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

  15. 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…

  16. 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…

  17. 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…

  18. 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…

  19. 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…

  20. 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…

  1. 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.

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. 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…

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Radon Policy in Finland, Achievements and Challenges

    SciTech Connect

    Arvela, Hannu; Maekelaeinen, Ilona; Reisbacka, Heikki

    2008-08-07

    Finland is a country of high indoor radon concentrations. Since 1980 the authority regulations, guidance, radon mapping and research work supporting decision making have been developed continuously. Clear regulations directed to citizens and authorities form the basis for radon policy. Active mapping work and measurement ordered by private home owners has resulted in 100.000 houses measured. National indoor radon data base forms a good basis for decision making, communication and research. The number of new houses provided with radon preventive constructions has increased remarkably. New radon campaigns has increased measurement and mitigation activity. Furher increasing of public awareness is the key challenge.

  17. Silica, silicosis and cancer in Finland.

    PubMed

    Partanen, T; Jaakkola, J; Tossavainen, A

    1995-01-01

    Approximately 100 000 Finnish workers are currently employed in jobs and tasks that may involve exposure to airborne silica dust. The major industries involved are mining and quarrying; production of glass, ceramics, bricks and other building materials; metal industry, particularly iron and steel founding; and construction. Over 1500 cases of silicosis have occurred in Finland since 1935. Tuberculosis has been a frequent complication of silicosis. Results of studies from several countries strongly suggest that silica dust also causes lung cancer. The results of the relevant Finnish epidemiologic and industrial hygiene studies addressing cancer risk and exposure to quartz dust are summarized. PMID:8929699

  18. Short-term dynamics of causal information transfer in thalamocortical networks during natural inputs and microstimulation for somatosensory neuroprosthesis

    PubMed Central

    Semework, Mulugeta; DiStasio, Marcello

    2014-01-01

    Recording the activity of large populations of neurons requires new methods to analyze and use the large volumes of time series data thus created. Fast and clear methods for finding functional connectivity are an important step toward the goal of understanding neural processing. This problem presents itself readily in somatosensory neuroprosthesis (SSNP) research, which uses microstimulation (MiSt) to activate neural tissue to mimic natural stimuli, and has the capacity to potentiate, depotentiate, or even destroy functional connections. As the aim of SSNP engineering is artificially creating neural responses that resemble those observed during natural inputs, a central goal is describing the influence of MiSt on activity structure among groups of neurons, and how this structure may be altered to affect perception or behavior. In this paper, we demonstrate the concept of Granger causality, combined with maximum likelihood methods, applied to neural signals recorded before, during, and after natural and electrical stimulation. We show how these analyses can be used to evaluate the changing interactions in the thalamocortical somatosensory system in response to repeated perturbation. Using LFPs recorded from the ventral posterolateral thalamus (VPL) and somatosensory cortex (S1) in anesthetized rats, we estimated pair-wise functional interactions between functional microdomains. The preliminary results demonstrate input-dependent modulations in the direction and strength of information flow during and after application of MiSt. Cortico-cortical interactions during cortical MiSt and baseline conditions showed the largest causal influence differences, while there was no statistically significant difference between pre- and post-stimulation baseline causal activities. These functional connectivity changes agree with physiologically accepted communication patterns through the network, and their particular parameters have implications for both rehabilitation and brain

  19. 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.

  20. The Discourse on Multicultural Education in Finland: Education for Whom?

    ERIC Educational Resources Information Center

    Holm, Gunilla; Londen, Monica

    2010-01-01

    Finland is experiencing increased immigration and therefore increased cultural diversity in its schools. This paper examines the multicultural education discourse in Finland by analysing the national and municipal curricula for the comprehensive school, educational policy documents and teacher education curricula. The focus is on how multicultural…

  1. Youth Suicide Trends in Finland, 1969-2008

    ERIC Educational Resources Information Center

    Lahti, Anniina; Rasanen, Pirkko; Riala, Kaisa; Keranen, Sirpa; Hakko, Helina

    2011-01-01

    Background: There are only a few recent studies on secular trends in child and adolescent suicides. We examine here trends in rates and methods of suicide among young people in Finland, where suicide rates at these ages are among the highest in the world. Methods: The data, obtained from Statistics Finland, consisted of all suicides (n = 901)…

  2. The Quality and Effectiveness of Confirmation Classes in Finland

    ERIC Educational Resources Information Center

    Niemela, Kati

    2006-01-01

    Every year some 90% of 15-year-olds in Finland attend confirmation classes in the Evangelical Lutheran Church of Finland, which is greater than the percentage of that age group belonging to the Church. What is behind the popularity of Finnish confirmation classes? This article scrutinizes the quality and effectiveness of confirmation classes.…

  3. ADHD in Finland and Types of Scandinavian Cooperation.

    ERIC Educational Resources Information Center

    Tapper, Marie-Louise; Michelsson, Katarina

    This paper reviews the history and current status of services to children with attention deficit hyperactivity disorder in Finland. It notes the availability of free or almost free health services in Finland and the resulting very low infant mortality rate. The history of attention deficit hyperactivity disorders (ADHD), termed "minimal brain…

  4. Cost-consequence analysis of cause of death investigation in Finland and in Denmark.

    PubMed

    Ylijoki-Sørensen, Seija; Boldsen, Jesper Lier; Lalu, Kaisa; Sajantila, Antti; Baandrup, Ulrik; Boel, Lene Warner Thorup; Ehlers, Lars Holger; Bøggild, Henrik

    2014-12-01

    The 1990s 12-16% total autopsy rate in Denmark has until now declined to 4%, while in Finland, it has remained between 25 and 30%. The decision to proceed with a forensic autopsy is based on national legislation, but it can be assumed that the financing of autopsies influences the decision process. Only little is known about the possible differences between health economics of Finnish and Danish cause of death investigation systems. The aims of this article were to analyse costs and consequences of Finnish and Danish cause of death investigations, and to develop an alternative autopsy practice in Denmark with another cost profile. Data on cause of death investigation systems and costs were derived from Departments of Forensic Medicine, Departments of Pathology, and the National Police. Finnish and Danish autopsy rates were calculated in unnatural (accident, suicide, homicide and undetermined intent) and natural (disease) deaths, and used to develop an alternative autopsy practice in Denmark. Consequences for society were analysed. The estimated unit cost (€) for one forensic autopsy is 3.2 times lower in Finland than in Denmark (€1400 versus €4420), but in Finland the salaries for forensic pathologists working at the National Institute for Health and Welfare are not included in the unit cost. The unit cost for one medical autopsy is also lower in Finland than in Denmark; €700 versus €1070. In our alternative practice in Denmark, the forensic autopsy rate was increased from 2.2% to 8.5%, and the medical autopsy rate from 2.4% to 5.8%. Costs per 10,000 deaths were estimated to be 50% (±25%) higher than now; i.e. €3,678,724 (2,759,112-4,598,336), but would result in a lower unit cost for forensic autopsies €3,094 (2,320-3,868) and for medical autopsies €749 (562-936). This practice would produce a higher accuracy of national mortality statistics, which, consequently, would entail higher quality in public health, an accurate basis for decision

  5. Assessment of atmospheric mercury emissions in Finland

    PubMed

    Mukherjee; Melanen; Ekqvist; Verta

    2000-10-01

    This paper is part of the study of atmospheric emissions of heavy metals conducted by the Finnish Environment Institute in collaboration with the Technical Research Centre of Finland (VTT) under the umbrella of the Finnish Ministry of the Environment. The scope of our study is limited solely to anthropogenic mercury that is emitted directly to the atmosphere. This article addresses emission factors and trends of atmospheric mercury emissions during the 1990s and is based mainly on the database of the Finnish Environmental Administration. In addition, data based on the measurements taken by the VTT regarding emission factors have been used to estimate emissions of mercury from the incineration of waste. The study indicates that the total emission of mercury has decreased from 1140 kg in 1990 to 620 kg in 1997, while industrial and energy production have been on the increase simultaneously. The 45% emission reduction is due to improved gas cleaning equipment, process changes, automation, the installation of flue gas desulfurization process in coal-fired power plants and strict pollution control laws. In the past, some authors have estimated a higher mercury emission in Finland. In this study, it is also observed that there are no big changes in the quality of raw materials. Estimated emission factors can be of great help to management for estimating mercury emissions and also its risk assessment. PMID:11032137

  6. Risk Assessment in Finland: Theory and Practice

    PubMed Central

    Pääkkönen, Rauno

    2010-01-01

    The Finnish risk assessment practice is based on the Occupational Safety and Health (OSH) Act aiming to improve working conditions in order maintain the employees' work ability, and to prevent occupational accidents and diseases. In practice there are hundreds of risk assessment methods in use. A simple method is used in small and medium sized enterprises and more complex risk evaluation methods in larger work places. Does the risk management function in the work places in Finland? According to our experience something more is needed. That is, understanding of common and company related benefits of risk management. The wider conclusion is that commitment for risk assessment in Finland is high enough. However, in those enterprises where OSH management was at an acceptable level or above it, there were also more varied and more successfully accomplished actions to remove or reduce the risks than in enterprises, where OSH management was in lower level. In risk assessment it is important to process active technical prevention and exact communication, increase work place attraction and increase job satisfaction and motivation. Investments in OSH are also good business. Low absenteeism due to illness or accidents increases directly the production results by improved quality and quantity of the product. In general Finnish studies have consistently shown that the return of an invested euro is three to seven-old. In national level, according to our calculations the savings could be even 20% of our gross national product. PMID:22953157

  7. Increased UV exposure in Finland in 1993.

    PubMed

    Jokela, K; Leszczynski, K; Visuri, R; Ylianttila, L

    1995-07-01

    Exceptionally low total ozone, up to 40% below the normal level, was measured over Northern Europe during winter and spring in 1992 and 1993. In 1993 the depletion persisted up to the end of May, resulting in a significant increase of biologically effective UV radiation. The increases were significantly smaller in 1992 and 1993 than in 1993. The UV exposure of the Finnish population was evaluated through measurements and theoretical calculations. The increase in measured erythemal (International Lighting Commission) UV falling onto horizontal surfaces on clear day was determined relative to model calculations for an average ozone amount. The increase was on average 10% from April to May 1993, and the maximal measured increase was 34%. Theoretical calculations for both erythemal and carcinogenic (Skin Cancer Utrecht--Philadelphia) UV indicated that in 1993 the theoretical annual increase to a vertical (cylinder) surface ranged from 8 to 13% in Finland. The reflection of UV from snow considerably increases facial UV doses in Northern Finland. PMID:7638253

  8. History of cosmic ray research in Finland

    NASA Astrophysics Data System (ADS)

    Usoskin, I. G.; Valtonen, E.; Vainio, R.; Tanskanen, P. J.; Aurela, A. M.

    2009-11-01

    The history of cosmic ray research in Finland can be traced back to the end of 1950s, when first ground-based cosmic ray measurements started in Turku. The first cosmic ray station was founded in Oulu in 1964 performing measurements of cosmic rays by a muon telescope, which was later complemented by a neutron monitor. Since the 1990s, several research centers and universities, such as The Finnish Meteorological Institute, Helsinki University of Technology, University of Oulu, University of Turku and University of Helsinki have been involved in space science projects, such as SOHO, AMS, Cluster, Cassini, BepiColombo, etc. At the same time, ground-based cosmic ray measurements have reached a new level, including a fully automatic on-line database in Oulu and a new muon measuring underground site in Pyhäsalmi. Research groups in Helsinki, Oulu and Turku have also extensive experience in theoretical investigations of different aspects of cosmic ray physics. Cosmic ray research has a 50-year long history in Finland, covering a wide range from basic long-running ground-based observations to high-technology space-borne instrumentation and sophisticated theoretical studies. Several generations of researchers have been involved in the study ensuring transfer of experience and building the recognized Finnish research school of cosmic ray studies.

  9. Risk assessment in Finland: theory and practice.

    PubMed

    Anttonen, Hannu; Pääkkönen, Rauno

    2010-09-01

    The Finnish risk assessment practice is based on the Occupational Safety and Health (OSH) Act aiming to improve working conditions in order maintain the employees' work ability, and to prevent occupational accidents and diseases. In practice there are hundreds of risk assessment methods in use. A simple method is used in small and medium sized enterprises and more complex risk evaluation methods in larger work places. Does the risk management function in the work places in Finland? According to our experience something more is needed. That is, understanding of common and company related benefits of risk management. The wider conclusion is that commitment for risk assessment in Finland is high enough. However, in those enterprises where OSH management was at an acceptable level or above it, there were also more varied and more successfully accomplished actions to remove or reduce the risks than in enterprises, where OSH management was in lower level. In risk assessment it is important to process active technical prevention and exact communication, increase work place attraction and increase job satisfaction and motivation. Investments in OSH are also good business. Low absenteeism due to illness or accidents increases directly the production results by improved quality and quantity of the product. In general Finnish studies have consistently shown that the return of an invested euro is three to seven-old. In national level, according to our calculations the savings could be even 20% of our gross national product. PMID:22953157

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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

  1. Information sources in science and technology in Finland

    NASA Technical Reports Server (NTRS)

    Haarala, Arja-Riitta

    1994-01-01

    Finland poses some problems to be overcome in the field of scientific and technical information: a small user community which makes domestic systems costly; great distances within the country between users and suppliers of information; great distances to international data systems and large libraries abroad; and inadequate collections of scientific and technical information. The national bibliography Fennica includes all books and journals published in Finland. Data base services available in Finland include: reference data bases in science and technology; data banks for decision making such as statistical time series or legal proceedings; national bibliographies; and library catalogs.

  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. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  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. 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

  16. 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.

  17. The Rehabilitation of Visually Impaired Persons in Finland.

    ERIC Educational Resources Information Center

    Ojamo, M.; And Others

    1990-01-01

    A profile is presented of the gender, age, and diagnoses of individuals with visual impairments in Finland. Services provided, current legislative measures, rehabilitation courses, and orientation and mobility training are also described. (JDD)

  18. Checklist of the Empidoidea of Finland (Insecta, Diptera)

    PubMed Central

    Kahanpää, Jere

    2014-01-01

    Abstract An updated checklist of the Atelestidae, Brachystomatidae, Dolichopodidae, Empididae and Hybotidae (Diptera) recorded from Finland is presented. The genera with uncertain placement within superfamily Empidoidea (= the Iteaphila group) are also included in this paper. PMID:25337016

  19. 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

  20. 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

  1. An autochthonous case of cystic echinococcosis in Finland, 2015.

    PubMed

    Hämäläinen, Sari; Kantele, Anu; Arvonen, Miika; Hakala, Tapio; Karhukorpi, Jari; Heikkinen, Jukka; Berg, Ensio; Vanamo, Kari; Tyrväinen, Erja; Heiskanen-Kosma, Tarja; Oksanen, Antti; Lavikainen, Antti

    2015-01-01

    We report a case of pulmonary cystic echinococcosis in a child from eastern Finland with no history of travelling abroad. The cyst was surgically removed and the organism molecularly identified as Echinococcus canadensis genotype G10. This parasite is maintained in eastern Finland in a sylvatic life cycle involving wolves and moose; in the present case, the infection was presumably transmitted by hunting dogs. PMID:26538367

  2. 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.

  3. 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}.

  4. Century-scale causal relationships between global dry/wet conditions and the state of the Pacific and Atlantic Oceans

    NASA Astrophysics Data System (ADS)

    Sun, Qiaohong; Miao, Chiyuan; AghaKouchak, Amir; Duan, Qingyun

    2016-06-01

    The Granger causality test is used to examine the effects of the El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and the North Atlantic Oscillation (NAO) on global dry/wet conditions. The results show robust relationships between dry/wet conditions and the ocean states, as assessed through a multi-index (standardized precipitation evapotranspiration index and standardized precipitation index) and multiscale (3 months and 12 months) evaluation. The influence of ENSO events is widespread, dominating about 38% of the global land surface (excluding Antarctica). Southern and western North America, northern South America, and eastern Russia are influenced by the PDO. The NAO influences not only dry/wet conditions in Europe but also dry/wet conditions in northern Africa. Similarly, climate variability in southern Europe and northern Africa may be due to the concurrence of the ENSO and the NAO. Knowledge of the spatial influence of ocean states on global dry/wet conditions is valuable for improving drought and flood forecasting.

  5. Laterality of Temporoparietal Causal Connectivity during the Prestimulus Period Correlates with Phonological Decoding Task Performance in Dyslexic and Typical Readers

    PubMed Central

    Liederman, Jacqueline; McGraw Fisher, Janet; Wu, Meng-Hung

    2012-01-01

    We examined how effective connectivity into and out of the left and right temporoparietal areas (TPAs) to/from other key cortical areas affected phonological decoding in 7 dyslexic readers (DRs) and 10 typical readers (TRs) who were young adults. Granger causality was used to compute the effective connectivity of the preparatory network 500 ms prior to presentation of nonwords that required phonological decoding. Neuromagnetic activity was analyzed within the low, medium, and high beta and gamma subbands. A mixed-model analysis determined whether connectivity to or from the left and right TPAs differed across connectivity direction (in vs. out), brain areas (right and left inferior frontal and ventral occipital–temporal and the contralateral TPA), reading group (DR vs. TR), and/or task performance. Within the low beta subband, better performance was associated with increased influence of the left TPA on other brain areas across both reading groups and poorer performance was associated with increased influence of the right TPA on other brain areas for DRs only. DRs were also found to have an increase in high gamma connectivity between the left TPA and other brain areas. This study suggests that hierarchal network structure rather than connectivity per se is important in determining phonological decoding performance. PMID:21980019

  6. Century-scale causal relationships between global drought conditions and the state of the Pacific and Atlantic Oceans

    NASA Astrophysics Data System (ADS)

    Sun, Qiaohong; Miao, Chiyuan; Duan, Qingyun

    2016-04-01

    Drought is one of the costliest and least understood natural hazards. The El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) are atmosphere-ocean coupled modes of climate variability that occur in the Pacific and Atlantic Oceans. In this study, the Granger causality test is used to examine the effects of ENSO, PDO, and NAO on global drought conditions. The results show robust relationships between drought conditions and the ocean states, as assessed through a multi-index (SPEI and SPI) and multiscalar (3-month and 12-month) evaluation. The influence of ENSO events is widespread, dominating about 40% of the global land droughts. Southern and western North America, northern South America, and eastern Russia are more influenced by PDO. Results show that NAO influence on drought is not restricted to Europe and includes northern Africa. The role of NAO is most evident at 3-month time scale. Moreover, the results provide evidence that drought conditions can be affected by multiple factors. ENSO and PDO may reinforce each other to dominate climate variability over North America and northern South America. Climate variability in southern Europe and northern Africa may be forced by the concurrence of ENSO and NAO. The spatial patterns of the influence of ocean states on global droughts provide valuable information for improving drought forecasting.

  7. Causal connectivity alterations of cortical-subcortical circuit anchored on reduced hemodynamic response brain regions in first-episode drug-naïve major depressive disorder

    PubMed Central

    Gao, Qing; Zou, Ke; He, Zongling; Sun, Xueli; Chen, Huafu

    2016-01-01

    Some efforts were done to investigate the disruption of brain causal connectivity networks involved in major depressive disorder (MDD) using Granger causality (GC) analysis. However, the homogenous hemodynamic response function (HRF) assumption over the brain may disturb the inference of temporal precedence. Here we applied a blind deconvolution approach to examine the altered HRF shape in first-episode, drug-naïve MDD patients. The regions with abnormal HRF shape in patients were chosen as seeds to detect the GC alterations in MDD. The results demonstrated significantly decreased magnitude of spontaneous hemodynamic response of the orbital frontal cortex (OFC) and the caudate nucleus (CAU) in MDD comparing to healthy controls, suggesting MDD patients likely had alterations in neurovascular coupling and cerebrovascular physiology in these two regions. GC mapping showed increased/decreased GC in OFC-/CAU centered networks in MDD. The outgoing GC values from OFC to anterior cingulate cortex and occipital regions were positively correlated with Hamilton Depression Scale (HAMD) scores, while the incoming GC from insula, middle and superior temporal gyrus to CAU were negatively correlated with HAMD scores of MDD. The abnormalities of directional connections in the cortico-subcortico-cerebellar network may lead to unbalanced integrating the emotional-related information for MDD, and further exacerbating depressive symptoms. PMID:26911651

  8. Children with well controlled epilepsy possess different spatio-temporal patterns of causal network connectivity during a visual working memory task.

    PubMed

    Protopapa, Foteini; Siettos, Constantinos I; Myatchin, Ivan; Lagae, Lieven

    2016-04-01

    Using spectral Granger causality (GC) we identified distinct spatio-temporal causal connectivity (CC) patterns in groups of control and epileptic children during the execution of a one-back matching visual discrimination working memory task. Differences between control and epileptic groups were determined for both GO and NOGO conditions. The analysis was performed on a set of 19-channel EEG cortical activity signals. We show that for the GO task, the highest brain activity in terms of the density of the CC networks is observed in α band for the control group while for the epileptic group the CC network seems disrupted as reflected by the small number of connections. For the NOGO task, the denser CC network was observed in θ band for the control group while widespread differences between the control and the epileptic group were located bilaterally at the left temporal-midline and parietal areas. In order to test the discriminative power of our analysis, we performed a pattern analysis approach based on fuzzy classification techniques. The performance of the classification scheme was evaluated using permutation tests. The analysis demonstrated that, on average, 87.6 % of the subjects were correctly classified in control and epileptic. Thus, our findings may provide a helpful insight on the mechanisms pertaining to the cognitive response of children with well controlled epilepsy and could potentially serve as "functional" biomarkers for early diagnosis. PMID:27066148

  9. Causal connectivity alterations of cortical-subcortical circuit anchored on reduced hemodynamic response brain regions in first-episode drug-naïve major depressive disorder.

    PubMed

    Gao, Qing; Zou, Ke; He, Zongling; Sun, Xueli; Chen, Huafu

    2016-01-01

    Some efforts were done to investigate the disruption of brain causal connectivity networks involved in major depressive disorder (MDD) using Granger causality (GC) analysis. However, the homogenous hemodynamic response function (HRF) assumption over the brain may disturb the inference of temporal precedence. Here we applied a blind deconvolution approach to examine the altered HRF shape in first-episode, drug-naïve MDD patients. The regions with abnormal HRF shape in patients were chosen as seeds to detect the GC alterations in MDD. The results demonstrated significantly decreased magnitude of spontaneous hemodynamic response of the orbital frontal cortex (OFC) and the caudate nucleus (CAU) in MDD comparing to healthy controls, suggesting MDD patients likely had alterations in neurovascular coupling and cerebrovascular physiology in these two regions. GC mapping showed increased/decreased GC in OFC-/CAU centered networks in MDD. The outgoing GC values from OFC to anterior cingulate cortex and occipital regions were positively correlated with Hamilton Depression Scale (HAMD) scores, while the incoming GC from insula, middle and superior temporal gyrus to CAU were negatively correlated with HAMD scores of MDD. The abnormalities of directional connections in the cortico-subcortico-cerebellar network may lead to unbalanced integrating the emotional-related information for MDD, and further exacerbating depressive symptoms. PMID:26911651

  10. 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…

  11. 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.

  12. 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…

  13. 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

  14. 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…

  15. 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'…

  16. 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.

  17. 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…

  18. 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

  19. 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…

  20. 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.…

  1. 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…

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. 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…

  9. 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…

  10. 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…

  11. 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

  12. Thermomagnetic properties of the Finland trityl radical

    PubMed Central

    Cage, Brant; McNeely, James Halley; Russek, Stephen E.; Halpern, Howard J.

    2009-01-01

    The Finland trityl paramagnet is characterized by magnetic susceptibility and a new form of quantitative electron paramagnetic resonance (EPR) that utilizes a superconducting quantum interference device (SQUID) as a detection method. This radical is of interest due to its use as a dynamic nuclear polarization agent as well as a potential magnetic refrigerant and quantum computing bit. The SQUID-EPR data show that the EPR linewidth of a concentrated trityl powder decreases dramatically from 4.4 to 1.4 mT as the temperature is increased from 1.8 to 10 K. The quantitative nature of SQUID-EPR is used to thermodynamically quantify the EPR energy transfer times and saturated fractions. At 95 GHz and 1.8 K, only 40% of the spins are in resonance at the onset of saturation. Conventional dc magnetic susceptibility over 1.8–150 K indicates an S=1∕2 Curie–Weiss relationship with little long range interaction. Magnetization versus applied field at 1.8 and 4 K fits a Brillouin function with >80% electronic polarization at a normalized field of gμBμ0H∕kT≈3. These results provide information required for theoretical modeling and engineering of the trityl radical for a wide range of applications. PMID:19529796

  13. [The plague in Finland in 1710].

    PubMed

    Engström, N G

    1994-01-01

    In the autumn of 1710 Helsinki was struck by the so-called oriental plague during four months. The infection was transferred by black rats which harboured fleas. The flea-bites caused boils. It was believed that the plague was air-borne, and the air was very humid that autumn. Big fires were lit in order to reduce the humidity, the purpose being to make it easier for the infected to breathe. Attempts were also made to dissect the boils. The carriers of the contamination came as refugees from Estland over the Gulf of Finland. The infection had spread from Turkey to Poland and Balticum after the defeat of the Finnish-Swedish army in the summer of 1709 at Poltava in Ucraine. Helsingfors (Helsinki) was struck extremely hard. About two-thirds of the inhabitants died of the pestilence. Some escaped by fleeing to the countryside. The plague spread through the country as far north as to Uleåborg (Oulu) and Cajana (Kajaani). Marketplaces became important centres of infection. With the advent of the frost in December the plague dwindled. At that time Helsinki was practically a dead town. PMID:11640321

  14. Phenology cameras observing boreal ecosystems of Finland

    NASA Astrophysics Data System (ADS)

    Peltoniemi, Mikko; Böttcher, Kristin; Aurela, Mika; Kolari, Pasi; Tanis, Cemal Melih; Linkosalmi, Maiju; Loehr, John; Metsämäki, Sari; Nadir Arslan, Ali

    2016-04-01

    Cameras have become useful tools for monitoring seasonality of ecosystems. Low-cost cameras facilitate validation of other measurements and allow extracting some key ecological features and moments from image time series. We installed a network of phenology cameras at selected ecosystem research sites in Finland. Cameras were installed above, on the level, or/and below the canopies. Current network hosts cameras taking time lapse images in coniferous and deciduous forests as well as at open wetlands offering thus possibilities to monitor various phenological and time-associated events and elements. In this poster, we present our camera network and give examples of image series use for research. We will show results about the stability of camera derived color signals, and based on that discuss about the applicability of cameras in monitoring time-dependent phenomena. We will also present results from comparisons between camera-derived color signal time series and daily satellite-derived time series (NVDI, NDWI, and fractional snow cover) from the Moderate Resolution Imaging Spectrometer (MODIS) at selected spruce and pine forests and in a wetland. We will discuss the applicability of cameras in supporting phenological observations derived from satellites, by considering the possibility of cameras to monitor both above and below canopy phenology and snow.

  15. Checklist of tapeworms (Platyhelminthes, Cestoda) of vertebrates in Finland

    PubMed Central

    Haukisalmi, Voitto

    2015-01-01

    Abstract A checklist of tapeworms (Cestoda) of vertebrates (fishes, birds and mammals) in Finland is presented, based on published observations, specimens deposited in the collections of the Finnish Museum of Natural History (Helsinki) and the Zoological Museum of the University of Turku, and additional specimens identified by the present author. The checklist includes 170 tapeworm species from 151 host species, comprising 447 parasite species/host species combinations. Thirty of the tapeworm species and 96 of the parasite/host species combinations have not been previously reported from Finland. The total number of tapeworm species in Finland (170 spp.) is significantly lower than the corresponding figure for the Iberian Peninsula (257 spp.), Slovakia (225 spp.) and Poland (279 spp.). The difference between Finland and the other three regions is particularly pronounced for anseriform, podicipediform, charadriiform and passeriform birds, reflecting inadequate and/or biased sampling of these birds in Finland. It is predicted that there are actually ca. 270 species of tapeworms in Finland, assuming that true number of bird tapeworms in Finland corresponds to that in other European countries with more comprehensive knowledge of the local tapeworm fauna. The other main pattern emerging from the present data is the seemingly unexplained absence in (northern) Fennoscandia of several mammalian tapeworms that otherwise have extensive distributions in the Holarctic region or in Eurasia, including the northern regions. Previously unknown type specimens, that is, the holotype of Bothrimonus nylandicus Schneider, 1902 (a junior synonym of Diplocotyle olrikii Krabbe, 1874) (MZH 127096) and the syntypes of Caryophyllaeides fennica (Schneider, 1902) (MZH 127097) were located in the collections of the Finnish Museum of Natural History. PMID:26668540

  16. Aquifer Properties in Hepokangas, Northern Finland

    NASA Astrophysics Data System (ADS)

    Pihlaja, M. Sc.

    2012-04-01

    Hepokangas study area is located in northern Finland, app. 60 km north-east of the city of Oulu. It consists of an esker ridge which ranges in elevation from 95 to 105 m.a.s.l. Consequently, all Quaternary deposits in the area have been influenced by erosional and depositional processes during two Baltic Sea stages (Ancylus Lake and Littorina Sea). Therefore, raised beaches are found on the esker slopes and fine grained sediments on the lowlands. The studied aquifer, the Hepokangas esker is part of an discontinuous chain of eskers which, in total, is about 100 km long and is elongated from north-west to south-east. The direction indicates that the esker was deposited by the melt waters during the latest phase of Weichselian glaciation. The primary part of the esker is located in the western segment of the area and a delta-like expansion of an esker is in the eastern part of the study area . Level of the ground water table (GWT) was measured at 14 ground water pipes which were located in varying parts of the Hepokangas formation. Ground penetrating radar (GPR) surveys were conducted on the primary part of the esker in order to determine internal structures and estimate permeability of the formation. Ground water flow directions were interpreted based on these measurements. The GWT varies from 91.91 to 97.98 m.a.s.l. Since the Hepokangas formation is surrounded by mires the height of the GWT decreased towards them. There was a water pumping station on the primary part of the formation, but no clear effect to the GWT could be seen to be caused by that. From the GPR results, some locations of the coarse grain sediments with high permeability were found.

  17. The development of railway safety in Finland.

    PubMed

    Silla, Anne; Kallberg, Veli-Pekka

    2012-03-01

    This study reviews the development of railway safety in Finland from 1959 to 2008. The results show that the level of safety has greatly improved over the past five decades. The total number of railway fatalities did not show any obvious decreasing or increasing trend during the first decade, but since the early 1970s the annual number of fatalities has decreased from about 100 to 20. The estimated overall annual reduction per year from 1970 to 2008 was 5.4% (with a 95% confidence interval from -8.2% to -2.6%). The reduction in subcategories per million train-kilometres from 1959 to 2008 was 4.4% per year for passengers, 8.3% for employees, 5.0% for road users at level crossings and 3.6% for others (mainly trespassers). The safety improvement for passengers and staff was probably influenced by the introduction of central locking of doors in passenger cars and improved procedures to protect railway employees working on the tracks. The number of road users killed at level crossings has fallen due to the installation of barriers and the construction of overpasses and underpasses at crossings with dense traffic, removal of level crossings, and an improvement of conditions such as visibility at crossings. The number of trespasser fatalities has seen the least decline. Key plans for the future include further reduction of the number of level crossings on the state railway network from the current roughly 3500-2200 by 2025, and involving communities in safety work related to railway trespassers. PMID:22269565

  18. Upgrading the Northern Finland Seismological Network

    NASA Astrophysics Data System (ADS)

    Narkilahti, Janne; Kozlovskaya, Elena; Silvennoinen, Hanna; Hurskainen, Riitta; Nevalainen, Jouni

    2016-04-01

    The Finnish National Seismic Network (FNSN) comprises national Helsinki University Seismological network (HE) ISUH and the Northern Finland Seismological Network (FN) hosted by the Sodankylä Geophysical Observatory (SGO) of the University of Oulu. The FN network currently consists of four real-time permanent stations equipped with Streckeisen STS-2 broad band seismometers that are recording continuous digital seismic data. At present, the network is a part of GEOFON Extended Virtual Network and of the ORFEUS Virtual European Broadband Seismograph Network. In the future, the network will be the part of EPOS-European Plate Observing System research infrastructure. As a part of EPOS project activities, the SGO started to upgrade their own network in 2014. The main target of the network upgrade is to increase the permanent station coverage in the European Arctic region, particularly behind the Polar Circle. Another target is to transform the network into a broadband seismic array capable to detect long-period seismic signals originating from seismic events in the Arctic. The first upgrade phase started in 2014, when two new stations were installed and now are working in the test regime. These stations are used as prototypes for testing seismic equipment and technical solutions for real-time data transmission and vault construction under cold climate conditions. The first prototype station is installed in a surface vault and equipped with Nanometrics Trillium 120P sensor, while the other one is installed in a borehole and equipped with Trillium Posthole seismometer. These prototype stations have provided to us valuable experience on the downhole and surface deployment of broadband seismic instruments. We also have been able to compare the capabilities and performance of high sensitivity broadband sensor deployed in borehole with that deployed in surface vault. The results of operation of prototype stations will be used in site selection and installation of four new

  19. 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:…

  20. 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…

  1. 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…

  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. 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…

  4. 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…

  5. 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…

  6. 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

  7. 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…

  8. 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…

  9. 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…

  10. 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...

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Checklist of the leaf-mining flies (Diptera, Agromyzidae) of Finland

    PubMed Central

    Kahanpää, Jere

    2014-01-01

    Abstract A checklist of the Agromyzidae (Diptera) recorded from Finland is presented. 279 (or 280) species are currently known from the country. Phytomyza linguae Lundqvist, 1947 is recorded as new to Finland. PMID:25337025

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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,…

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. Age and Meanings of Violence: Women's Experiences of Partner Violence in Finland

    ERIC Educational Resources Information Center

    Piispa, Minna

    2004-01-01

    The first survey carried out in Finland specifically to study men's violence against women showed that partner violence is quite common in Finland and it is directed especially toward young women. The statistical findings don't support the idea that violence has become more widespread in Finland. Life situation factors that are usually viewed as…

  13. 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

  14. 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

  15. Checklist of the family Syrphidae (Diptera) of Finland

    PubMed Central

    Haarto, Antti; Kerppola, Sakari

    2014-01-01

    Abstract A checklist of the Syrphidae (Diptera) recorded from Finland. Three species of Syrphidae, Platycheirus modestus Ide, 1926, Cheilosia barovskii (Stackelberg, 1930) and Mallota tricolor Loew, 1871, are published as new to the Finnish fauna. Platycheirus modestus is also new to the Palaearctic. PMID:25337020

  16. Students' Attitudes towards Craft and Technology in Iceland and Finland

    ERIC Educational Resources Information Center

    Thorsteinsson, Gísli; Ólafsson, Brynjar; Autio, Ossi

    2012-01-01

    Craft education in both Finland and Iceland originated over 140 years ago and was influenced by the Scandinavian Sloyd pedagogy. Since then, the subject has moved away from craft and towards technology, with the aim being to increase students' technological abilities. In the beginning, the subject largely focused on the students copying artefacts,…

  17. Children's Early Numeracy in Finland and Iran

    ERIC Educational Resources Information Center

    Aunio, Pirjo; Korhonen, Johan; Bashash, Laaya; Khoshbakht, Fariba

    2014-01-01

    This research investigates similarities and differences in young children's early numeracy skills related to age, nationality and gender. The participants were five- to seven-year-old children from Finland and Iran. Early numeracy was investigated by using tasks measuring number-related relational skills (e.g. comparison, one-to-one…

  18. Epidemiology of Frontotemporal Lobar Degeneration in Northern Finland

    PubMed Central

    Luukkainen, Laura; Bloigu, Risto; Moilanen, Virpi; Remes, Anne Marja

    2015-01-01

    Background Frontotemporal lobar degeneration (FTLD) is responsible for as many as every fifth case of early-onset dementia. Very few epidemiological studies of FTLD have been conducted; there are no published epidemiological data of FTLD from Finland or the other Nordic countries. The C9ORF72 expansion-associated FTLD is common in Finland; thus, the prevalence of FTLD is expected to be high in this population. Methods We retrospectively evaluated the incidence and prevalence of FTLD in university hospital settings in Northern Finland. Results The mean 1-year incidence of FTLD was 5.54/100,000 (range 1.9-11.3/100,000) in the population aged 45-65 years. The prevalence of FTLD in the same age group was 20.5/100,000. Conclusion The incidence and prevalence of FTLD in Finland seem to be the highest in Europe. However, studies from different countries may not be directly mutually comparable due to methodological issues. PMID:26675285

  19. Evaluating the Quality of the Child Care in Finland

    ERIC Educational Resources Information Center

    Hujala, Eeva; Fonsen, Elina; Elo, Janniina

    2012-01-01

    In this study we examine parents' and teachers' perceptions of the early childhood education and care (ECEC) quality in Finland. The study is based on the paradigm of inclusionary quality and the assessment is based on the quality evaluation model. The parents and teachers assess the quality to be good. The strength of the quality was the effect…

  20. Teaching Popular Music in Finland: What's Up, What's Ahead?

    ERIC Educational Resources Information Center

    Vakeva, Lauri

    2006-01-01

    This article describes the history and current situation of popular music pedagogy in Finland. While popular music is widely accepted in the curriculum, there are differences in its application in the comprehensive schools and music institutions. Popular styles were first introduced into Finnish music education by secondary school music teachers;…

  1. Thematic Review on Adult Learning: Finland. Background Report.

    ERIC Educational Resources Information Center

    Organisation for Economic Cooperation and Development, Paris (France).

    In international comparisons, participation in adult learning in Finland is high. Work or career development is the main reason for participation. Persons starting with greater educational attainment participate in adult learning opportunities more. Roots of adult education and training (AET) lie in liberal education; those of occupational AET in…

  2. Infection with Possible Novel Parapoxvirus in Horse, Finland, 2013

    PubMed Central

    Hautaniemi, Maria; Syrjä, Pernilla; Knuuttila, Anna; Putkuri, Niina; Coulter, Lesley; McInnes, Colin J.; Vapalahti, Olli; Huovilainen, Anita; Kinnunen, Paula M.

    2016-01-01

    A horse in Finland exhibited generalized granulomatous inflammation and severe proliferative dermatitis. After euthanization, we detected poxvirus DNA from a skin lesion sample. The virus sequence grouped with parapoxviruses, closely resembling a novel poxvirus detected in humans in the United States after horse contact. Our findings indicate horses may be a reservoir for zoonotic parapoxvirus. PMID:27315302

  3. Teaching Linear Equations: Case Studies from Finland, Flanders and Hungary

    ERIC Educational Resources Information Center

    Andrews, Paul; Sayers, Judy

    2012-01-01

    In this paper we compare how three teachers, one from each of Finland, Flanders and Hungary, introduce linear equations to grade 8 students. Five successive lessons were videotaped and analysed qualitatively to determine how teachers, each of whom was defined against local criteria as effective, addressed various literature-derived…

  4. Early Years Educators in Finland and England: Issues of Professionality.

    ERIC Educational Resources Information Center

    Moriarty, Viv

    2000-01-01

    Semi-structured interviews were conducted to examine early years educators' views of their professional role in England and Finland, related to the role of parents during early years education. Findings suggested that Finnish educators had adopted understanding of professionalism based more closely on notions of complexity and democracy than…

  5. Molecular Epidemiology of Tuberculosis in Finland, 2008-2011

    PubMed Central

    Smit, Pieter Willem; Haanperä, Marjo; Rantala, Pirre; Couvin, David; Lyytikäinen, Outi; Rastogi, Nalin; Ruutu, Petri; Soini, Hanna

    2013-01-01

    In industrialized countries the majority of tuberculosis (TB) cases are linked to immigration. In Finland, most cases are still Finnish born but the number of foreign born cases is steadily increasing. In this 4-year population based study, the TB situation in Finland was characterized by a genotypic analysis of Mycobacterium tuberculosis isolates. A total of 1048 M. tuberculosis isolates (representing 99.4% of all culture positive cases) were analyzed by spoligotyping and MIRU. Spoligotype lineages belonging to the Euro-American family were predominant among the Finnish isolates, particularly T (n=346, 33.0%) and Haarlem (n=237, 22.6%) strains. The lineage signature was unknown for 130 (12.4%) isolates. Out of the 17 multi-drug resistant TB strains, 10 (58.8%) belonged to the Beijing lineage. In total, 23 new SIT designations were given and 51 orphan strains were found, of which 58 patterns were unique to Finland. Phylogeographical TB mapping as compared to neighboring countries showed that the population structure in Finland most closely resembled that observed in Sweden. By combining spoligotyping and MIRU results, 98 clusters comprising 355 isolates (33.9%) were found. Only 10 clusters contained both Finnish and foreign born cases. In conclusion, a large proportion of the M. tuberculosis isolates were from Finnish born elderly patients. Moreover, many previously unidentified spoligotype profiles and isolates belonging to unknown lineages were encountered. PMID:24386443

  6. Children as Consumers of Historical Culture in Finland

    ERIC Educational Resources Information Center

    Rantala, Jukka

    2011-01-01

    The article examines the reception of history by 7-10-year-old children in Finland and the role of historical culture in the formation of children's conceptions of the past. It scrutinizes how history is used to build individual and collective identities and bring significance to the past in children's everyday lives. Interviews with 174 pupils in…

  7. World Perspective Case Descriptions on Educational Programs for Adults: Finland.

    ERIC Educational Resources Information Center

    Virtala, Mirja; And Others

    This document contains eight case studies of the following adult education programs in Finland: (1) an experiment combining classroom teaching and distance education and one that studied the effects of offering art courses at different levels in 1982-1985 (Virtala); (2) cooperative programs since 1981 between municipal and city levels in Mikkeli…

  8. Segregation, Integration, Inclusion--The Ideology and Reality in Finland

    ERIC Educational Resources Information Center

    Kivirauma, Joel; Klemela, Kirsi; Rinne, Risto

    2006-01-01

    In this paper, we try to examine the classical sociological points of special education, especially the organizational form of special education, social background of students and the minority status of students. The material of the study was collected mostly during 2003 from one large city in Finland. This city has more than a 100-year-long…

  9. Swedish Immersion in the Early Years in Finland

    ERIC Educational Resources Information Center

    Björklund, Siv; Mård-Miettinen, Karita; Savijärvi, Marjo

    2014-01-01

    Immersion education in Finland is a one-way (monolingual) early total Swedish programme for Finnish-speaking students. This immersion provision is offered at kindergarten level (ages 3-5), at preschool (age 6) and at primary levels (grades 1-9). Here, a brief synthesis of Finnish research studies on the early years in Swedish immersion is first…

  10. Young Children's Number Sense in Finland, Hong Kong and Singapore

    ERIC Educational Resources Information Center

    Aunio, Pirjo; Ee, Jessie; Lim, Swee Eng Audrey; Hautamaki, Jarkko; Van Luit, Johannes E. H.

    2004-01-01

    This study examines young children's number sense in subjects from Finland (n =254), Hong Kong (n =246), and Singapore (n =130). Chinese, English and Finnish versions of the Early Numeracy Test (ENT; Van Luit et al., 1994) were used. Two highly correlated aspects of number sense were measured, one reflecting children's abilities to organize and…

  11. Multicultural Education in Finland: Renewed Intercultural Competencies to the Rescue?

    ERIC Educational Resources Information Center

    Dervin, Fred; Paatela-Nieminen, Martina; Kuoppala, Kaisa; Riitaoja, Anna-Leena

    2012-01-01

    This paper reviews discourses on multicultural education and the concept of intercultural competencies in the European and Nordic country of Finland. We focus on their present uses and perceptions by decision-makers, researchers, and also student teachers. Some prognosis for the future is made based on a short case study from art teacher education…

  12. Teacher Education in Italy, Germany, England, Sweden and Finland

    ERIC Educational Resources Information Center

    Ostinelli, Giorgio

    2009-01-01

    This article presents a brief analysis of teacher education in five European countries: Italy, Germany, England, Sweden and Finland. In the post-industrial world, the sense of teaching has profoundly changed, influenced by a rapidly evolving socio-economic context. The responses given by each country are different, but two tendencies emerge: on…

  13. Thematic Review on Adult Learning: Finland. Country Note. Revised.

    ERIC Educational Resources Information Center

    Organisation for Economic Cooperation and Development, Paris (France).

    This country note analyzes main issues concerning adult learning and policy responses in Finland. Section 2 describes the political, economic, and social context in which adult learning fits. Sections 3-6 follow these four themes impinging on adult participation in learning: inadequate incentives and motivations; complex pathways between learning…

  14. Infection with Possible Novel Parapoxvirus in Horse, Finland, 2013.

    PubMed

    Airas, Niina; Hautaniemi, Maria; Syrjä, Pernilla; Knuuttila, Anna; Putkuri, Niina; Coulter, Lesley; McInnes, Colin J; Vapalahti, Olli; Huovilainen, Anita; Kinnunen, Paula M

    2016-07-01

    A horse in Finland exhibited generalized granulomatous inflammation and severe proliferative dermatitis. After euthanization, we detected poxvirus DNA from a skin lesion sample. The virus sequence grouped with parapoxviruses, closely resembling a novel poxvirus detected in humans in the United States after horse contact. Our findings indicate horses may be a reservoir for zoonotic parapoxvirus. PMID:27315302

  15. My Lifelong Learning Realm: An Autoethnography Experiential Learning in Finland

    ERIC Educational Resources Information Center

    Rajbhandari, Mani Man Singh

    2011-01-01

    My journey to write autoethnography report started with inclination to learn cultural and social phenomena in Finland. This was my realm of learning through experiential learning. The ontological philosophy was perceived through objectivistic and subjectivistic approaches. The lifelong experiential learning realm was a benchmark for me to perceive…

  16. Career Burnout and Its Relationship to Couple Burnout in Finland.

    ERIC Educational Resources Information Center

    Laes, Timo; Laes, Tuula

    This study is part of cross cultural research on the relationship between career and couple burnout in six countries (England, Finland, Israel, Portugal, Spain, and the USA.) This pilot study presents first results of Finnish data. Female elementary school teachers (N=56) and male students (N=70) in academic professional education completed the…

  17. Language Acquisition in the Swedish-Speaking Minority in Finland.

    ERIC Educational Resources Information Center

    Brunell, A. Viking

    1991-01-01

    Documents the differences in language acquisition and school achievement between Finnish- and Swedish-speaking students in Finland's comprehensive school systems. Discusses the need for language maintenance and enrichment measures in both out-of-school and in-school environments. (SR)

  18. 75 FR 30431 - Carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-01

    ... 207), as most recently amended at 74 FR 2847 (January 16, 2009). \\1\\ No response to this request for... carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden (70 FR 39734). The Commission is conducting reviews... employment statute for Federal employees, and Commission rule 201.15(b)(19 CFR 201.15(b)), 73 FR 24609 (May...

  19. Learning Practices of Femininity through Gendered Craft Education in Finland

    ERIC Educational Resources Information Center

    Kokko, Sirpa

    2009-01-01

    This paper discusses the processes and practices that link crafts and gender in the upbringing and education of girls. The paper is based on a study conducted among female primary school trainee teachers in Finland. The data are comprised of their experiences with crafts as schoolgirls. The methods of the study were memory work and writing of…

  20. Needs for Rural Research in the Northern Finland Context

    ERIC Educational Resources Information Center

    Muilu, Toivo

    2010-01-01

    The aim of this paper is to discuss the needs and demands which rural research faces at the interface between research and development. The case study area is northern Finland, which constitutes the most remote and sparsely populated areas of the European Union. This paper is based on the tradition of rural research since the 1980s in connection…

  1. 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

  2. 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

  3. Acid sulfate soils are an environmental hazard in Finland

    NASA Astrophysics Data System (ADS)

    Pihlaja, Jouni

    2016-04-01

    Acid sulfate soils (ASS) create significant threats to the environment on coastal regions of the Baltic Sea in Finland. The sediments were deposited during the ancient Litorina Sea phase of the Baltic Sea about 7500-4500 years ago. Finland has larger spatial extent of the ASS than any other European country. Mostly based on anthropogenic reasons (cultivation, trenching etc.) ASS deposits are currently being exposed to oxygen which leads to chemical reaction creating sulfuric acid. The acidic waters then dissolve metals form the soil. Acidic surface run off including the metals are then leached into the water bodies weakening the water quality and killing fish or vegetation. In constructed areas acidic waters may corrode building materials. Geological Survey of Finland (GTK) is mapping ASS deposits in Finland. The goal is to map a total of 5 million hectares of the potentially ASS affected region. It has been estimated that the problematic Litorina Sea deposits, which are situated 0-100 m above the recent Baltic Sea shoreline, cover 500 000 hectares area. There are several phases in mapping. The work begins at the office with gathering the existing data, interpreting airborne geophysical data and compiling a field working plan. In the field, quality of the soil is studied and in uncertain cases samples are taken to laboratory analyses. Also electrical conductivity and pH of soil and water are measured in the field. Laboratory methods include multielemental determinations with ICP-OES, analyses of grain size and humus content (LOI), and incubation. So far, approximately 60 % of the potential ASS affected regions in Finland are mapped. Over 15 000 sites have been studied in the field and 4000 laboratory analyses are done. The spatial database presented in the scale of 1: 250 000 can be viewed at the GTK's web pages (http://gtkdata.gtk.fi/hasu/index.html).

  4. 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.…

  5. 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…

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  7. Lifelong Learning in Finland: The Extent to Which Vocational Education and Training Policy Is Nurturing Lifelong Learning in Finland. CEDEFOP Panorama Series.

    ERIC Educational Resources Information Center

    Nyyssola, Kari; Hamalainen, Kimmo

    The extent to which vocational education and training policy is nurturing lifelong learning in Finland was examined. The analysis focused on the following issues: the political and structural framework of education in Finland; mechanisms supporting lifelong learning; and pedagogical solutions and learning environments facilitating lifelong…

  8. 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.

  9. 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

  10. 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

  11. 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

  12. The network of causal interactions for beta oscillations in the pedunculopontine nucleus, primary motor cortex, and subthalamic nucleus of walking parkinsonian rats.

    PubMed

    Li, Min; Zhou, Ming; Wen, Peng; Wang, Qiang; Yang, Yong; Xiao, Hu; Xie, Zhengyuan; Li, Xing; Wang, Ning; Wang, Jinyan; Luo, Fei; Chang, Jingyu; Zhang, Wangming

    2016-08-01

    Oscillatory activity has been well-studied in many structures within cortico-basal ganglia circuits, but it is not well understood within the pedunculopontine nucleus (PPN), which was recently introduced as a potential target for the treatment of gait and postural impairments in advanced stages of Parkinson's disease (PD). To investigate oscillatory activity in the PPN and its relationship with oscillatory activity in cortico-basal ganglia circuits, we simultaneously recorded local field potentials in the PPN, primary motor cortex (M1), and subthalamic nucleus (STN) of 6-hydroxydopamine (6-OHDA)-induced hemiparkinsonian rats during resting and walking. After analysis of power spectral density, coherence, and partial Granger causality, three major findings emerged: 1) after 6-OHDA lesions, beta band oscillations were enhanced in all three regions during walking; 2) the direction of information flow for beta oscillations among the three structures was STN→M1, STN→PPN, and PPN→M1; 3) after the treatment of levodopa, beta activity in the three regions was reduced significantly and the flow of beta band was also abrogated. Our results suggest that beta activity in the PPN is transmitted from the basal ganglia and probably comes from the STN, and the STN plays a dominant role in the network of causal interactions for beta activity. Thus, the STN may be a potential source of aberrant beta band oscillations in PD. Levodopa can inhibit beta activity in the PPN of parkinsonian rats but cannot relieve parkinsonian patients' axial symptoms clinically. Therefore, beta oscillations may not be the major cause of axial symptoms. PMID:27163550

  13. Acute Human Inkoo and Chatanga Virus Infections, Finland

    PubMed Central

    Kantele, Anu; Levanov, Lev; Kivistö, Ilkka; Brummer-Korvenkontio, Markus; Vaheri, Antti; Vapalahti, Olli

    2016-01-01

    Inkoo virus (INKV) and Chatanga virus (CHATV), which are circulating in Finland, are mosquitoborne California serogroup orthobunyaviruses that have a high seroprevalence among humans. Worldwide, INKV infection has been poorly described, and CHATV infection has been unknown. Using serum samples collected in Finland from 7,961 patients suspected of having viral neurologic disease or Puumala virus infection during the summers of 2001–2013, we analyzed the samples to detect California serogroup infections. IgM seropositivity revealed 17 acute infections, and cross-neutralization tests confirmed presence of INKV or CHATV infections. All children (<16 years of age) with INKV infection were hospitalized; adults were outpatients with mild disease, except for 1 who was hospitalized with CHATV infection. Symptoms included fever, influenza-like illness, nausea or vomiting, disorientation, nuchal rigidity, headache, drowsiness, and seizures. Although many INKV and CHATV infections appear to be subclinical, these viruses can cause more severe disease, especially in children. PMID:27088268

  14. Economic hardship and suicide mortality in Finland, 1875-2010.

    PubMed

    Korhonen, Marko; Puhakka, Mikko; Viren, Matti

    2016-03-01

    We investigate the determinants of suicide in Finland using annual data for consumption and suicides from 1860 to 2010. Instead of using some ad hoc measures of cyclical movements of the economy, we build our analysis on a more solid economic theory. A key feature is the habit persistence in preferences, which provides a way to measure individual well-being and predict suicide. We estimate time series of habit levels and develop an indicator (the hardship index) to describe the economic hardship of consumers. The higher the level of the index, the worse off consumers are. As a rational response to such a bad situation, some consumers might commit suicide. We employ the autoregressive distributed lags cointegration method and find that our index works well in explaining the long-term behavior of people committing suicide in Finland. PMID:25446657

  15. Heat Wave–Associated Vibriosis, Sweden and Finland, 2014

    PubMed Central

    Trinanes, Joaquin A.; Salmenlinna, Saara; Löfdahl, Margareta; Siitonen, Anja; Taylor, Nick G.H.; Martinez-Urtaza, Jaime

    2016-01-01

    During summer 2014, a total of 89 Vibrio infections were reported in Sweden and Finland, substantially more yearly infections than previously have been reported in northern Europe. Infections were spread across most coastal counties of Sweden and Finland, but unusually, numerous infections were reported in subarctic regions; cases were reported as far north as 65°N, ≈100 miles (160 km) from the Arctic Circle. Most infections were caused by non-O1/O139 V. cholerae (70 cases, corresponding to 77% of the total, all strains were negative for the cholera toxin gene). An extreme heat wave in northern Scandinavia during summer 2014 led to unprecedented high sea surface temperatures, which appear to have been responsible for the emergence of Vibrio bacteria at these latitudes. The emergence of vibriosis in high-latitude regions requires improved diagnostic detection and clinical awareness of these emerging pathogens. PMID:27314874

  16. Heat Wave-Associated Vibriosis, Sweden and Finland, 2014.

    PubMed

    Baker-Austin, Craig; Trinanes, Joaquin A; Salmenlinna, Saara; Löfdahl, Margareta; Siitonen, Anja; Taylor, Nick G H; Martinez-Urtaza, Jaime

    2016-07-01

    During summer 2014, a total of 89 Vibrio infections were reported in Sweden and Finland, substantially more yearly infections than previously have been reported in northern Europe. Infections were spread across most coastal counties of Sweden and Finland, but unusually, numerous infections were reported in subarctic regions; cases were reported as far north as 65°N, ≈100 miles (160 km) from the Arctic Circle. Most infections were caused by non-O1/O139 V. cholerae (70 cases, corresponding to 77% of the total, all strains were negative for the cholera toxin gene). An extreme heat wave in northern Scandinavia during summer 2014 led to unprecedented high sea surface temperatures, which appear to have been responsible for the emergence of Vibrio bacteria at these latitudes. The emergence of vibriosis in high-latitude regions requires improved diagnostic detection and clinical awareness of these emerging pathogens. PMID:27314874

  17. Mercury pollution near an industrial source in southwest Finland

    SciTech Connect

    Hynninen, V.; Lodenius, M.

    1986-02-01

    Mercury is very sparse in Finnish rocks and soils. Some mercury occurs in the ore of the Outokumpu mine, SE Finland. Metal ore from this mine is refined in the metallurgical plants at Kokkola and Harjavalta. Elevated mercury contents have been observed in the environment of the plant at Kokkola but no data have been published about the possible mercury contamination around the Harjavalta plant.

  18. 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

  19. Health reform in Finland: current proposals and unresolved challenges.

    PubMed

    Saltman, Richard B; Teperi, Juha

    2016-07-01

    The Finnish health care system is widely respected for its pilot role in creating primary-care-led health systems. In the early 1990s, however, a severe economic downturn in Finland reduced public funding and weakened the Finnish system's deeply decentralized model of health care administration. Recent Bank of Finland projections forecasting several decades of slow economic growth, combined with the impact of an aging population, appear to make major reform of the existing public system inevitable. Over the last several years, political attention has focused mostly on administrative consolidation inside the public sector, particularly integration of health and social services. Current proposals call for a reformed health sector governance structure based on a new meso-level configuration of public administration. In addition, Finland's national government has proposed replacing the current multi-channel public funding structure (which includes health insurance subsidies for occupational health services) with a single-channel public funding structure. This commentary examines several key issues involved in reforming the delivery structure of the Finnish health care system. It also explores possible alternative strategies to reform current funding arrangements. The article concludes with a brief discussion of implications from this Finnish experience for the wider health reform debate. PMID:26865494

  20. Green energy products in the United Kingdom, Germany and Finland

    NASA Astrophysics Data System (ADS)

    Hast, Aira; McDermott, Liisa; Järvelä, Marja; Syri, Sanna

    2014-12-01

    In liberalized electricity markets, suppliers are offering several kinds of voluntary green electricity products marketed as environmentally friendly. This paper focuses on the development of these voluntary markets at household level in the UK, Germany and Finland. Since there are already existing renewable energy policies regulating and encouraging the use of renewable energy, it is important to consider whether voluntary products offer real additional benefits above these policies. Problems such as double counting or re-marketing hydropower produced in existing plants are identified. According to our study, the demand varies between countries: in Germany the number of green electricity customers has increased and is also higher than in the UK or Finland. Typically the average additional cost to consumer from buying green electricity product instead of standard electricity product is in the range of 0-5% in all studied countries, although the level of price premium depends on several factors like electricity consumption. Case study of Finland and literature show that the impacts of green energy are not solely environmental. Renewable energy can benefit local public policy.

  1. Growing season precipitation in Finland under recent and projected climate

    NASA Astrophysics Data System (ADS)

    Ylhäisi, J. S.; Tietäväinen, , H.; Peltonen-Sainio, P.; Venäläinen, A.; Eklund, J.; Räisänen, J.; Jylhä, K.

    2010-07-01

    The past and projected future precipitation sum in May-September for two areas in Finland, one located in the south-west (SW) and the other in the north-east (NE), is studied using 13 regional climate simulations and three observational datasets. The conditions in the present-day climate for agricultural crop production are far more favourable in the south-western part of the country than the more continental north-eastern Finland. Based on a new high-resolution observational precipitation dataset for Finland (FMI_grid), with a resolution of 10×10 km, the only statistically significant past long-term (1908-2008) precipitation tendencies in the two study regions are positive. Differences between FMI_grid and two other observational datasets during 1961-2000 are rather large in the NE, whereas in the SW the datasets agree better. Observational uncertainties stem from the interpolation and sampling errors. The projected increases in precipitation in the early stage of the growing season would be most favourable for agricultural productivity, but the projected increases in August and September might be harmful. Model projections for the future indicate a statistically significant increase in precipitation for most of the growing season by 2100, but the distribution of precipitation within the growing season is not necessarily the most optimal.

  2. 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,…

  3. 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…

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. 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…

  9. 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…

  10. 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…

  11. 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.

  12. 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…

  13. 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

  14. 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

  15. 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…

  16. 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…

  17. 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…

  18. 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…

  19. 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-…

  20. 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…

  1. 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…

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. Household economic resources, labour-market advantage and health problems - a study on causal relationships using prospective register data.

    PubMed

    Aittomäki, Akseli; Martikainen, Pekka; Laaksonen, Mikko; Lahelma, Eero; Rahkonen, Ossi

    2012-10-01

    Our aim was to find out whether the associations between health and both individual and household economic position reflected a causal effect on health of household affluence and consumption potential. We attempted to separate this effect from health-selection effects, in other words the potential effect of health on economic position, and from various effects related to occupational position and prestige that might correlate with the economic indicators. We made a distinction between individual labour-market advantage and household economic resources in order to reflect these theoretical definitions. Our aim was to test and compare two hypotheses: 1) low household economic resources lead to an increase in health problems later on, and 2) health problems are disadvantageous on the labour market, and consequently decrease the level of economic resources. We used prospective register data obtained from the databases of Statistics Finland and constituting an 11-per-cent random sample of the Finnish population in 1993-2006. Health problems were measured in terms of sickness allowance paid by the Finnish Social Insurance Institution, household economic resources in terms of household-equivalent disposable income and taxable wealth, and labour-market advantage in terms of individual taxable income and months of unemployment. We used structural equation models (n = 211,639) to examine the hypothesised causal pathways. Low household economic resources predicted future health problems, and health problems predicted future deterioration in labour-market advantage. The effect of economic resources on health problems was somewhat stronger. These results suggest that accumulated exposure to low economic resources leads to increasing health problems, and that this causal mechanism is a more significant source of persistent health inequalities than health problems that bring about a permanent decrease in economic resources. PMID:22727652

  7. A causal net approach to relativistic quantum mechanics

    NASA Astrophysics Data System (ADS)

    Bateson, R. D.

    2012-05-01

    In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.

  8. 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.

  9. Subjective spacetime derived from a causal histories approach

    NASA Astrophysics Data System (ADS)

    Gunji, Yukio-Pegio; Haruna, Taichi; Uragami, Daisuke; Nishikawa, Asaki

    2009-10-01

    The internal description of spacetime can reveal ambiguity regarding an observer’s perception of the present, where an observer can refer to the present as if he were outside spacetime while actually existing in the present. This ambiguity can be expressed as the compatibility between an element and a set, and is here called a/{a}-compatibility. We describe a causal set as a lattice and a causal history as a quotient lattice, and implement the a/{a}-compatibility in the framework of a causal histories approach. This leads to a perpetual change of a pair of causal set and causal history, and can be used to describe subjective spacetime including the déjà vu experience and/or schizophrenic time.

  10. 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

  11. Ecosystem and atmospheric measurements in ICOS-Finland

    NASA Astrophysics Data System (ADS)

    Kaukolehto, Marjut

    2013-04-01

    The global mean temperature has increased and will continue to increase in the 21st century due to the increased concentrations of greenhouse gases such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in the atmosphere (IPCC, 2007). Understanding about the driving forces of climate change requires full quantification of the greenhouse gas (GHG) emissions and sinks by long term and high precision observations in the atmosphere as well as on the land and ocean surfaces. There are major research challenges such as 1) what is the regional distribution of GHG fluxes, 2) how does environmental factors and human intervention impact the exchange of GHG, and 3) how will the sources and sinks of GHGes change in future. Integrated Carbon Observation System (ICOS) has received funding by the EU to develop a strategic plan for constructing a European research infrastructure to provide the long-term atmospheric and flux observations required to understand the present state and predict the future behaviour of the global carbon cycle and GHG emissions as well as to monitor and assess the effectiveness of carbon sequestration in GHG emission reduction activities. The legal seat and the Head Office of the forthcoming ICOS organisation, European Research Infrastructure Consortium (ERIC), will be located in Finland, with secondary node in France. Finland has a role as a Nordic Hub and mobile laboratory operator of the Atmospheric Thematic Centre (ATC), which is led by France. The backbones of the ICOS research infrastructure are the national measurement networks for atmospheric, ecosystem and oceanic measurements. The ICOS-Finland is established by three national partners: University of Helsinki, Finnish Meteorological Institute, and University of Eastern Finland, and it will operate 14 ICOS measurement stations: four Level 1 atmospheric measurement sites; two Level 1 ecosystem measurement sites; one Level 2 ecosystem measurement site; and seven associate ecosystem

  12. Impacts of peatland forestation on regional climate conditions in Finland

    NASA Astrophysics Data System (ADS)

    Gao, Yao; Markkanen, Tiina; Backman, Leif; Henttonen, Helena M.; Pietikäinen, Joni-Pekka; Laaksonen, Ari

    2014-05-01

    Climate response to anthropogenic land cover change happens more locally and occurs on a shorter time scale than the global warming due to increased GHGs. Over the second half of last Century, peatlands were vastly drained in Finland to stimulate forest growth for timber production. In this study, we investigate the biophysical effects of peatland forestation on near-surface climate conditions in Finland. For this, the regional climate model REMO, developed in Max Plank Institute (currently in Climate Service Center, Germany), provides an effective way. Two sets of 15-year climate simulations were done by REMO, using the historic (1920s; The 1st Finnish National Forest Inventory) and present-day (2000s; the 10th Finnish National Forest Inventory) land cover maps, respectively. The simulated surface air temperature and precipitation were then analyzed. In the most intensive peatland forestation area in Finland, the differences in monthly averaged daily mean surface air temperature show a warming effect around 0.2 to 0.3 K in February and March and reach to 0.5 K in April, whereas a slight cooling effect, less than 0.2 K, is found from May till October. Consequently, the selected snow clearance dates in model gridboxes over that area are advanced 0.5 to 4 days in the mean of 15 years. The monthly averaged precipitation only shows small differences, less than 10 mm/month, in a varied pattern in Finland from April to September. Furthermore, a more detailed analysis was conducted on the peatland forestation area with a 23% decrease in peatland and a 15% increase in forest types. 11 day running means of simulated temperature and energy balance terms, as well as snow depth were averaged over 15 years. Results show a positive feedback induced by peatland forestation between the surface air temperature and snow depth in snow melting period. This is because the warmer temperature caused by lower surface albedo due to more forest in snow cover period leads to a quicker and

  13. Civil Engineering Applications of Ground Penetrating Radar in Finland

    NASA Astrophysics Data System (ADS)

    Pellinen, Terhi; Huuskonen-Snicker, Eeva; Olkkonen, Martta-Kaisa; Eskelinen, Pekka

    2014-05-01

    Ground penetrating radar (GPR) has been used in Finland since 1980's for civil engineering applications. First applications in this field were road surveys and dam inspections. Common GPR applications in road surveys include the thickness evaluation of the pavement, subgrade soil evaluation and evaluation of the soil moisture and frost susceptibility. Since the 1990's, GPR has been used in combination with other non-destructive testing (NDT) methods in road surveys. Recently, more GPR applications have been adopted, such as evaluating bridges, tunnels, railways and concrete elements. Nowadays, compared with other countries GPR is relatively widely used in Finland for road surveys. Quite many companies, universities and research centers in Finland have their own GPR equipment and are involved in the teaching and research of the GPR method. However, further research and promotion of the GPR techniques are still needed since GPR could be used more routinely. GPR has been used to evaluate the air void content of asphalt pavements for years. Air void content is an important quality measure of pavement condition for both the new and old asphalt pavements. The first Finnish guideline was released in 1999 for the method. Air void content is obtained from the GPR data by measuring the dielectric value as continuous record. To obtain air void content data, few pavement cores must be taken for calibration. Accuracy of the method is however questioned because there are other factors that affect the dielectric value of the asphalt layer, in addition to the air void content. Therefore, a research project is currently carried out at Aalto University in Finland. The overall objective is to investigate if the existing GPR technique used in Finland is accurate enough to be used as QC/QA tool in assessing the compaction of asphalt pavements. The project is funded by the Finnish Transport Agency. Further research interests at Aalto University include developing new microwave asphalt

  14. 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

  15. Simplifying Causal Complexity: How Interactions between Modes of Causal Induction and Information Availability Lead to Heuristic-Driven Reasoning

    ERIC Educational Resources Information Center

    Grotzer, Tina A.; Tutwiler, M. Shane

    2014-01-01

    This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame…

  16. 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…

  17. 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

  18. Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models

    NASA Astrophysics Data System (ADS)

    Sizochenko, Natalia; Gajewicz, Agnieszka; Leszczynski, Jerzy; Puzyn, Tomasz

    2016-03-01

    In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal analysis of multivariate data. Methods of causal discovery have been applied for broader physical insight into mechanisms of action and interpretation of the developed nano-QSAR models. Previously developed nano-QSAR models for toxicity of 17 nano-sized metal oxides towards E. coli bacteria have been validated by means of the causality criteria. Using the descriptors confirmed by the causal technique, we have developed new models consistent with the straightforward causal-reasoning account. It was proven that causal inference methods are able to provide a more robust mechanistic interpretation of the developed nano-QSAR models.In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal

  19. Applying Causal Discovery to the Output of Climate Models - What Can We Learn from the Causal Signatures?

    NASA Astrophysics Data System (ADS)

    Ebert-Uphoff, I.; Hammerling, D.; Samarasinghe, S.; Baker, A. H.

    2015-12-01

    The framework of causal discovery provides algorithms that seek to identify potential cause-effect relationships from observational data. The output of such algorithms is a graph structure that indicates the potential causal connections between the observed variables. Originally developed for applications in the social sciences and economics, causal discovery has been used with great success in bioinformatics and, most recently, in climate science, primarily to identify interaction patterns between compound climate variables and to track pathways of interactions between different locations around the globe. Here we apply causal discovery to the output data of climate models to learn so-called causal signatures from the data that indicate interactions between the different atmospheric variables. These causal signatures can act like fingerprints for the underlying dynamics and thus serve a variety of diagnostic purposes. We study the use of the causal signatures for three applications: 1) For climate model software verification we suggest to use causal signatures as a means of detecting statistical differences between model runs, thus identifying potential errors and supplementing the Community Earth System Model Ensemble Consistency Testing (CESM-ECT) tool recently developed at NCAR for CESM verification. 2) In the context of data compression of model runs, we will test how much the causal signatures of the model outputs changes after different compression algorithms have been applied. This may result in additional means to determine which type and amount of compression is acceptable. 3) This is the first study applying causal discovery simultaneously to a large number of different atmospheric variables, and in the process of studying the resulting interaction patterns for the two aforementioned applications, we expect to gain some new insights into their relationships from this approach. We will present first results obtained for Applications 1 and 2 above.

  20. Causal inference with a quantitative exposure.

    PubMed

    Zhang, Zhiwei; Zhou, Jie; Cao, Weihua; Zhang, Jun

    2016-02-01

    The current statistical literature on causal inference is mostly concerned with binary or categorical exposures, even though exposures of a quantitative nature are frequently encountered in epidemiologic research. In this article, we review the available methods for estimating the dose-response curve for a quantitative exposure, which include ordinary regression based on an outcome regression model, inverse propensity weighting and stratification based on a propensity function model, and an augmented inverse propensity weighting method that is doubly robust with respect to the two models. We note that an outcome regression model often imposes an implicit constraint on the dose-response curve, and propose a flexible modeling strategy that avoids constraining the dose-response curve. We also propose two new methods: a weighted regression method that combines ordinary regression with inverse propensity weighting and a stratified regression method that combines ordinary regression with stratification. The proposed methods are similar to the augmented inverse propensity weighting method in the sense of double robustness, but easier to implement and more generally applicable. The methods are illustrated with an obstetric example and compared in simulation studies. PMID:22729475