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Is there a causal relation between construction activity and the Portuguese economy? An econometric empirical application

Nunes, Alcina; Lopes, Jorge; Balsa, Carlos
Fonte: Marie Ashwin, Normandy Business School - France Publicador: Marie Ashwin, Normandy Business School - France
Tipo: Conferência ou Objeto de Conferência
Português
Relevância na Pesquisa
46.55%
It has long been recognised that the role of the construction industry in a country’s national economy goes beyond its share in national output. Existing paradigms on the structural change of the construction industry as national economy develops over time have been evolving from an approach that stresses the role of construction investment (indeed physical capital) as an engine of economic growth to one where the pattern of the evolution of the industry should follow that of the general economy. Using time–series data drawn from the United Nations national accounts databases, this study applies an econometric methodology to assess the validity of the underlying propositions in a high-income economy - Portugal - over the long period of 38 years. With the availability of long and reliable time-series data and the development of econometric methodology related to the study of economic relationships between variables a new set of studies has emerged. Indeed, making use of the most recent innovations in the literature of unit root tests, this paper uses the Granger causality methodology to investigate the relationship between construction activity, measured by the construction value added, and the Portuguese aggregate economy measured by its Gross Domestic Product (GDP). The issues of concern here are whether the construction sector and the aggregate economy are interdependent and whether construction activity contributes to economic growth and/or economic growth contributes to the dynamics of the construction industry activity. This kind of economic research has not been applied...

Is there a causal relationship between construction activity and the portuguese economy? An econometric empirical application.

Nunes, Alcina; Lopes, Jorge; Balsa, Carlos
Fonte: Academic Publishing Limited Publicador: Academic Publishing Limited
Tipo: Conferência ou Objeto de Conferência
Português
Relevância na Pesquisa
46.55%
It has long been recognised that the role of the construction industry in a country’s national economy goes beyond its share in national output. Existing paradigms on the structural change of the construction industry as national economy develops over time have been evolving from an approach that stresses the role of construction investment (indeed physical capital) as an engine of economic growth to one where the pattern of the evolution of the industry should follow that of the general economy. Using time–series data drawn from the United Nations national accounts databases, this study applies an econometric methodology to assess the validity of the underlying propositions in Portugal. With the availability of long and reliable time-series data and the development of econometric methodology related to the study of economic relationships between variables a new set of studies has emerged. Indeed, making use of the most recent innovations in the literature of unit root tests, this paper uses the Granger causality methodology to investigate the relationship between construction activity, measured by the construction value added, and the Portuguese aggregate economy measured by its Gross Domestic Product (GDP). The issues of concern here are whether the construction sector and the aggregate economy are interdependent and whether construction activity contributes to economic growth and/or economic growth contributes to the dynamics of the construction industry activity. This kind of economic research has not been applied...

Analysis of the causal relation between construction activity and the gross domestic product of two neighbouring economies : Portugal and Spain

Nunes, Alcina; Lopes, Jorge; Balsa, Carlos
Fonte: Associação Portuguesa de Desenvolvimento Regional - APDR Publicador: Associação Portuguesa de Desenvolvimento Regional - APDR
Tipo: Conferência ou Objeto de Conferência
Português
Relevância na Pesquisa
46.55%
It has long been recognised that the role of the construction industry in a country’s national economy goes beyond its share in national output. Using time–series data drawn from the United Nations national accounts databases, this study applies the econometric Granger causality methodology to investigate the relationship between construction activity, measured by the construction value added, and the Gross Domestic Product (GDP) of two neighbouring economies – Portugal and Spain. In a comparison basis, the paper intends to identify the existence of a causal relation between the construction sector and each one of the aggregate economies. In particular, it tries to verify if the construction activity contributes to economic growth and/or economic growth contributes to the dynamics of the construction industry activity in these two countries. For both countries is find evidence that GDP growth leads the growth in the construction sector, in the short and medium-run. The opposite is not observed.

EFFECTIVE CONNECTIVITY DURING HAPTIC PERCEPTION: A STUDY USING GRANGER CAUSALITY ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE IMAGING DATA

Deshpande, Gopikrishna; Hu, Xiaoping; Stilla, Randall; Sathian, K.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
Although it is accepted that visual cortical areas are recruited during touch, it remains uncertain whether this depends on top-down inputs mediating visual imagery or engagement of modality-independent representations by bottom-up somatosensory inputs. Here we addressed this by examining effective connectivity in humans during haptic perception of shape and texture with the right hand. Multivariate Granger causality analysis of functional magnetic resonance imaging (fMRI) data was conducted on a network of regions that were shape- or texture-selective. A novel network reduction procedure was employed to eliminate connections that did not contribute significantly to overall connectivity. Effective connectivity during haptic perception was found to involve a variety of interactions between areas generally regarded as somatosensory, multisensory, visual and motor, emphasizing flexible cooperation between different brain regions rather than rigid functional separation. The left postcentral sulcus (PCS), left precentral gyrus and right posterior insula were important sources of connections in the network. Bottom-up somatosensory inputs from the left PCS and right posterior insula fed into visual cortical areas, both the shape-selective right lateral occipital complex (LOC) and the texture-selective right medial occipital cortex (probable V2). In addition...

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

Gow, David W.; Segawa, Jennifer A.; Ahlfors, Seppo P.; Lin, Fa-Hsuan
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
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.

Investigation of relationships between fMRI brain networks in the spectral domain using ICA and Granger causality reveals distinct differences between schizophrenia patients and healthy controls

Demirci, Oguz; Stevens, Michael C.; Andreasen, Nancy C.; Michael, Andrew; Liu, Jingyu; White, Tonya; Pearlson, Godfrey D.; Clark, Vincent P.; Calhoun, Vince D.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
Functional network connectivity (FNC) is an approach that examines the relationships between brain networks (as opposed to functional connectivity (FC) that focuses upon the relationships between single voxels). FNC may help explain the complex relationships between distributed cerebral sites in the brain and possibly provide new understanding of neurological and psychiatric disorders such as schizophrenia. In this paper, we use independent component analysis (ICA) to extract the time courses of spatially independent components and then use these in Granger causality test (GCT) to investigate causal relationships between brain activation networks. We present results using both simulations and fMRI data of 155 subjects obtained during two different tasks. Unlike previous research, causal relationships are presented over different portions of the frequency spectrum in order to differentiate high and low frequency effects and not merged in a scalar. The results obtained using Sternberg item recognition paradigm (SIRP) and auditory oddball (AOD) tasks showed FNC differentiations between schizophrenia and control groups, and explained how the two groups differed during these tasks. During the SIRP task, secondary visual and cerebellum activation networks served as hubs and included most complex relationships between the activated regions. Secondary visual and temporal lobe activations replaced these components during the AOD task.

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

Zhou, Zhenyu; Ding, Mingzhou; Chen, Yonghong; Wright, Paul; Lu, Zuhong; Liu, Yijun
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
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.

A Note on Inferring Acyclic Network Structures Using Granger Causality Tests*

Nagarajan, Radhakrishnan
Fonte: Berkeley Electronic Press Publicador: Berkeley Electronic Press
Tipo: Artigo de Revista Científica
Publicado em 25/03/2009 Português
Relevância na Pesquisa
46.55%
Granger causality (GC) and its extension have been used widely to infer causal relationships from multivariate time series generated from biological systems. GC is ideally suited for causal inference in bivariate vector autoregressive process (VAR). A zero magnitude of the upper or lower off-diagonal element(s) in a bivariate VAR is indicative of lack of causal relationship in that direction resulting in true acyclic structures. However, in experimental settings, statistical tests, such as F-test that rely on the ratio of the mean-squared forecast errors, are used to infer significant GC relationships. The present study investigates acyclic approximations within the context of bi-directional two-gene network motifs modeled as bivariate VAR. The fine interplay between the model parameters in the bivariate VAR, namely: (i) transcriptional noise variance, (ii) autoregulatory feedback, and (iii) transcriptional coupling strength that can give rise to discrepancies in the ratio of the mean-squared forecast errors is investigated. Subsequently, their impact on statistical power is investigated using Monte Carlo simulations. More importantly, it is shown that one can arrive at acyclic approximations even for bi-directional networks for suitable choice of process parameters...

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

Krumin, Michael; Shoham, Shy
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method.

Granger Causality Relationships between Local Field Potentials in an Animal Model of Temporal Lobe Epilepsy

Cadotte, Alex J.; DeMarse, Thomas B.; Mareci, Thomas H.; Parekh, Mansi; Talathi, Sachin S.; Hwang, Dong-Uk; Ditto, William L.; Ding, Mingzhou; Carney, Paul R.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
An understanding of the in vivo spatial emergence of abnormal brain activity during spontaneous seizure onset is critical to future early seizure detection and closed-loop seizure prevention therapies. In this study, we use Granger causality (GC) to determine the strength and direction of relationships between local field potentials (LFPs) recorded from bilateral microelectrode arrays in an intermittent spontaneous seizure model of chronic temporal lobe epilepsy before, during, and after Racine grade partial onset generalized seizures. Our results indicate distinct patterns of directional GC relationships within the hippocampus, specifically from the CA1 subfield to the dentate gryus, prior to and during seizure onset. Our results suggest sequential and hierarchical temporal relationships between the CA1 and dentate gyrus within and across hippocampal hemispheres during seizure. Additionally, our analysis suggests a reversal in the direction of GC relationships during seizure, from an abnormal pattern to more anatomically expected pattern. This reversal correlates well with the observed behavioral transition from tonic to clonic seizure in time-locked video. These findings highlight the utility of GC to reveal dynamic directional temporal relationships between multichannel LFP recordings from multiple brain regions during unprovoked spontaneous seizures.

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

Hamilton, J. Paul; Chen, Gang; Thomason, Moriah E.; Schwartz, Mirra E.; Gotlib, Ian H.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
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...

Granger Causality Mapping during Joint Actions Reveals Evidence for Forward Models That Could Overcome Sensory-Motor Delays

Kokal, Idil; Keysers, Christian
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 21/10/2010 Português
Relevância na Pesquisa
46.55%
Studies investigating joint actions have suggested a central role for the putative mirror neuron system (pMNS) because of the close link between perception and action provided by these brain regions [1], [2], [3]. In contrast, our previous functional magnetic resonance imaging (fMRI) experiment demonstrated that the BOLD response of the pMNS does not suggest that it directly integrates observed and executed actions during joint actions [4]. To test whether the pMNS might contribute indirectly to the integration process by sending information to brain areas responsible for this integration (integration network), here we used Granger causality mapping (GCM) [5]. We explored the directional information flow between the anterior sites of the pMNS and previously identified integrative brain regions. We found that the left BA44 sent more information than it received to both the integration network (left thalamus, right middle occipital gyrus and cerebellum) and more posterior nodes of the pMNS (BA2). Thus, during joint actions, two anatomically separate networks therefore seem effectively connected and the information flow is predominantly from anterior to posterior areas of the brain. These findings suggest that the pMNS is involved indirectly in joint actions by transforming observed and executed actions into a common code and is part of a generative model that could predict the future somatosensory and visual consequences of observed and executed actions in order to overcome otherwise inevitable neural delays.

Measuring Granger Causality between Cortical Regions from Voxelwise fMRI BOLD Signals with LASSO

Tang, Wei; Bressler, Steven L.; Sylvester, Chad M.; Shulman, Gordon L.; Corbetta, Maurizio
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels...

Re-entrant Projections Modulate Visual Cortex in Affective Perception: Evidence From Granger Causality Analysis

Keil, Andreas; Sabatinelli, Dean; Ding, Mingzhou; Lang, Peter J.; Ihssen, Niklas; Heim, Sabine
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /02/2009 Português
Relevância na Pesquisa
46.55%
Re-entrant modulation of visual cortex has been suggested as a critical process for enhancing perception of emotionally arousing visual stimuli. This study explores how the time information inherent in large-scale electrocortical measures can be used to examine the functional relationships among the structures involved in emotional perception. Granger causality analysis was conducted on steady-state visual evoked potentials elicited by emotionally arousing pictures flickering at a rate of 10 Hz. This procedure allows one to examine the direction of neural connections. Participants viewed pictures that varied in emotional content, depicting people in neutral contexts, erotica, or interpersonal attack scenes. Results demonstrated increased coupling between visual and cortical areas when viewing emotionally arousing content. Specifically, intraparietal to inferotemporal and precuneus to calcarine connections were stronger for emotionally arousing picture content. Thus, we provide evidence for re-entrant signal flow during emotional perception, which originates from higher tiers and enters lower tiers of visual cortex.

Recovering Directed Networks in Neuroimaging Datasets Using Partially Conditioned Granger Causality

Wu, Guo-Rong; Liao, Wei; Stramaglia, Sebastiano; Chen, Huafu; Marinazzo, Daniele
Fonte: Mary Ann Liebert, Inc. Publicador: Mary Ann Liebert, Inc.
Tipo: Artigo de Revista Científica
Publicado em /06/2013 Português
Relevância na Pesquisa
46.55%
Recovering directed pathways of information transfer between brain areas is an important issue in neuroscience and helps to shed light on the brain function in several physiological and cognitive states. Granger causality (GC) analysis is a valuable tool to detect directed dynamical connectivity, and it is being increasingly used. Unfortunately, this approach encounters some limitations in particularly when applied to neuroimaging datasets, often consisting in short and noisy data and for which redundancy plays an important role. In this article, we address one of these limitations, namely, the computational and conceptual problems arising when conditional GC, necessary to disambiguate direct and mediated influences, is used on short and noisy datasets of many variables, as it is typically the case in some electroencephalography (EEG) protocols and in functional magnetic resonance imaging (fMRI). We show that considering GC in the framework of information theory we can limit the conditioning to a limited number of variables chosen as the most informative, obtaining more stable and reliable results both in EEG and fMRI data.

Multivariate Granger Causality Analysis of Acupuncture Effects in Mild Cognitive Impairment Patients: An fMRI Study

Chen, Shangjie; Bai, Lijun; Xu, Maosheng; Wang, Fang; Yin, Liang; Peng, Xuming; Chen, Xinghua; Shi, Xuemin
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.55%
Evidence from clinical reports has indicated that acupuncture has a promising effect on mild cognitive impairment (MCI). However, it is still unknown that by what way acupuncture can modulate brain networks involving the MCI. In the current study, multivariate Granger causality analysis (mGCA) was adopted to compare the interregional effective connectivity of brain networks by varying needling depths (deep acupuncture, DA; superficial acupuncture, SA) and at different cognitive states, which were the MCI and healthy control (HC). Results from DA at KI3 in MCI showed that the dorsolateral prefrontal cortex and hippocampus emerged as central hubs and had significant causal influences with each other, but significant in HC for DA. Moreover, only several brain regions had remarkable causal interactions following SA in MCI and even few brain regions following SA in HC. Our results indicated that acupuncture at KI3 at different cognitive states and with varying needling depths may induce distinct reorganizations of effective connectivities of brain networks, and DA at KI3 in MCI can induce the strongest and more extensive effective connectivities related to the therapeutic effect of acupuncture in MCI. The study demonstrated the relatively functional specificity of acupuncture at KI3 in MCI...

Video Sensor-Based Complex Scene Analysis with Granger Causality

Fan, Yawen; Yang, Hua; Zheng, Shibao; Su, Hang; Wu, Shuang
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 11/10/2013 Português
Relevância na Pesquisa
46.55%
In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes. Under our framework, a low-level codebook is generated by an adaptive quantization with respect to the activeness criterion. The Hierarchical Dirichlet Processes (HDP) model is then applied to automatically cluster low-level features into atomic activities. Afterwards, the dynamic behaviors of the activities are represented as a multivariate point-process. The pair-wise relationships between activities are explicitly captured by the non-parametric Granger causality analysis, from which the activity interactions and temporal dependencies are discovered. Then, each video clip is labeled by one of the activity interactions. The results of the real-world traffic datasets show that the proposed method can achieve a high quality classification performance. Compared with traditional K-means clustering, a maximum improvement of 19.19% is achieved by using the proposed causal grouping method.

Analysing connectivity with Granger causality and dynamic causal modelling

Friston, Karl; Moran, Rosalyn; Seth, Anil K
Fonte: Current Biology Publicador: Current Biology
Tipo: Artigo de Revista Científica
Publicado em /04/2013 Português
Relevância na Pesquisa
46.55%
► A brief introduction to the analysis of directed connectivity in brain networks. ► An overview of advances in Granger causality and dynamic causal modelling. ► A comparative evaluation of both approaches in terms of their pros and cons.

Granger Causality Network Reconstruction of Conductance-Based Integrate-and-Fire Neuronal Systems

Zhou, Douglas; Xiao, Yanyang; Zhang, Yaoyu; Xu, Zhiqin; Cai, David
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 19/02/2014 Português
Relevância na Pesquisa
46.55%
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...

Extending Granger causality to nonlinear systems

Ancona, Nicola; Marinazzo, Daniele; Stramaglia, Sebastiano
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 03/05/2004 Português
Relevância na Pesquisa
46.66%
We consider extension of Granger causality to nonlinear bivariate time series. In this frame, 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. Not all the nonlinear prediction schemes are suitable to evaluate causality, indeed not all of them allow to quantify how much the knowledge of the other time series counts to improve prediction error. We present a novel approach with bivariate time series modelled by a generalization of radial basis functions and show its application to a pair of unidirectionally coupled chaotic maps and to a physiological example.; Comment: 8 pages, 4 figures