Measure Of Interdependence Research Articles

Evidence of interdependence and contagion using a frequency domain framework

This paper proposes a new measure of contagion, based on the frequency analysis of causality developed recently by Breitung and Candelon [Breitung, J., Candelon, B. 2006. Testing for short and long-run causality: a frequency domain approach, Journal of Econometrics, 12, 363–378.]. This approach handles several of the statistical problems identified in the literature. It also permits clear differentiation between temporary and permanent shifts in cross-market linkages: the first case is contagion while the second one is simply a measure of interdependence among markets. With this new approach, we examine the “Tequila” and Asian crises and find evidence of contagion for both. During the Asian crisis, higher interdependence has also contributed to the diffusion of the crisis in Asia.

Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non‐crisis and crisis episodes, including trends and bursts in spillovers; both turn out to be empirically important. In particular, in an analysis of 19 global equity markets from the early 1990s to the present, we find striking evidence of divergent behaviour in the dynamics of return spillovers vs. volatility spillovers: return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts.

Characterizing Dynamic Functional Connectivity Across Sleep Stages from EEG

Following a nonlinear dynamics approach, we investigated the emergence of functional clusters which are related with spontaneous brain activity during sleep. Based on multichannel EEG traces from 10 healthy subjects, we compared the functional connectivity across different sleep stages. Our exploration commences with the conjecture of a small-world patterning, present in the scalp topography of the measured electrical activity. The existence of such a communication pattern is first confirmed for our data and then precisely determined by means of two distinct measures of non-linear interdependence between time-series. A graph encapsulating the small-world network structure along with the relative interdependence strength is formed for each sleep stage and subsequently fed to a suitable clustering procedure. Finally the delineated graph components are comparatively presented for all stages revealing novel attributes of sleep architecture. Our results suggest a pivotal role for the functional coupling during the different stages and indicate interesting dynamic characteristics like its variable hemispheric asymmetry and the isolation between anterior and posterior cortical areas during REM.

Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: Comparison among different strategies based onknearest neighbors

We compare the different existing strategies of mutual nonlinear prediction regarding their ability to assess the coupling strength and directionality of the interactions in bivariate time series. Under the common framework of k -nearest neighbor local linear prediction, we test three approaches based on cross prediction, mixed prediction, and predictability improvement. The measures of interdependence provided by these approaches are first evaluated on short realizations of bivariate time series generated by coupled Henon models, investigating also the effects of noise. The usefulness of the three mutual nonlinear prediction schemes is then assessed in a common physiological application during known conditions of interaction-i.e., the analysis of the interdependence between heart rate and arterial pressure variability in healthy humans during supine resting and passive head-up tilting. Based on both simulation results and physiological interpretability of cardiovascular results, we conclude that cross prediction is valuable to quantify the coupling strength and predictability improvement to elicit directionality of the interactions in short and noisy bivariate time series.

Estimating Granger causality after stimulus onset: A cautionary note

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.

Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non-crisis and crisis episodes, including trends and bursts in spillovers, and both turn out to be empirically important. In particular, in an analysis of sixteen global equity markets from the early 1990s to the present, we find striking evidence of divergent behavior in the dynamics of return spillovers vs. volatility spillovers: Return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts.

Estimating nonlinear interdependences in dynamical systems using cellular nonlinear networks

We propose a method for estimating nonlinear interdependences between time series using cellular nonlinear networks. Our approach is based on the nonlinear dynamics of interacting nonlinear elements. We apply it to time series of coupled nonlinear model systems and to electroencephalographic time series from an epilepsy patient, and we show that an accurate approximation of symmetric and asymmetric realizations of a nonlinear interdependence measure can be achieved, thus allowing one to detect the strength and direction of couplings.

Network Polarization, Network Interdependence, and International Conflict, 1816–2002

This study examines the effect of polarization and interdependence on systemic conflict. It argues that both polarization and interdependence must be conceptualized in terms of different types of relations among states and that different relationships would reflect varied levels of polarization and inter-dependence. Accordingly, this study develops general measures of network polarization and interdependence that allow measurement of these concepts over a wide array of international relations. Hypotheses are deduced from the realist and liberal paradigms about how alliance polarization, trade polarization, and cultural polarization affect systemic conflict. Likewise, hypotheses are deduced regarding the expected effects of strategic and economic interdependence on conflict. These hypotheses are tested using data on alliance, trade, linguistic, and religious networks over the period 1816–2002. The findings suggest that alliance polarization and strategic interdependence increase the amount of systemic conflict, while trade polarization and economic interdependence have a dampening effect on the amount of conflict in the international system. The theoretical implications of these results are discussed.

The role of corticothalamic coupling in human temporal lobe epilepsy

The EEG activity of the thalamus and temporal lobe structures (hippocampus, entorhinal cortex and neocortex) was obtained using intracerebral recordings (stereoelectroencephalography, SEEG) performed in patients with TLE seizures undergoing pre-surgical evaluation. Synchrony was studied using a statistical measure of SEEG signal interdependencies (non-linear correlation). The results demonstrated an overall increase of synchrony between the thalamus and temporal lobe structures during seizures. Moreover, although there was great inter-individual variability, we found that values from seizure onset period were significantly higher than values from the background period (P = 0.001). Values at the end of seizure were significantly higher than values from the seizure onset (P < 0.0001). Several indices were also defined in order to correlate some clinical features to the degree of coupling between cortical structures and the thalamus. In patients with mesial TLE seizures, a correlation was found between the degree of thalamocortical synchrony and the presence of an early loss of consciousness but not with other clinical parameters. In addition, surgical prognosis seemed better in patients with low values of thalamocortical couplings at the seizure onset. This report demonstrates that the thalamus and remote cortical structures synchronize their activity during TLE seizures and suggest that the extension of the epileptogenic network to the thalamus is a potential important factor determining surgical prognosis.

Parent-child value transmission among Chinese immigrants to North America: The case of traditional mate preferences.

Parent-child similarities in traditional mate preferences were examined in Chinese immigrants to North America. Adult children (n = 63) rated their preferred mate characteristics. Children then completed measures of interdependence, family allocentrism, Chinese identity, and Asian values. Their parents (n = 63) also rated their own preferences for their child's spouse and their own Asian values. Parents reported greater preference for traditional mate characteristics than did their children. Parents' preferences were related to parents' own Asian values. Children's traditional mate preferences were predicted by their parents' preferences and their own family allocentrism. Family allocentrism was a marginally significant partial mediator of parent's influence on children's preferences. Family connectedness may, therefore, facilitate intergenerational transmission of values in immigrant Asian families.

Detecting event-related time-dependent directional couplings

Nonlinear interdependence measures can be used to detect directional couplings between stationary dynamical systems from a pair of signals measured from them. For many dynamics, however, intermittent directional couplings arise in causal relation to distinct events on timescales that are often too short to be resolved by nonlinear interdependence measures. On the other hand, in many experimental settings signals are measured for multiple instances of such events. We demonstrate how these multiple realizations can be exploited to reliably detect event-related time-dependent directional couplings. For this purpose, we propose the general concept of time-resolved causal statistics derived from embeddings across multiple realizations of time-dependent dynamics. Surrogates constructed by permuting the order of realizations can be used to test specified null hypotheses. We adapt a conventional nonlinear interdependence measure to serve as a time-resolved causal statistic and apply it to exemplary coupled Lorenz dynamics. This approach allows detecting event-related time-dependent directional couplings based on only a few tens of realizations. Changes of the coupling direction can be detected within one oscillation of the dynamics. Beyond this particular application, any metric bivariate or univariate measure can be adapted to serve as time-resolved causal statistics to characterize various aspects of event-related time-dependent dynamics.

Asymmetric extreme interdependence in emerging equity markets

AbstractWe assess the extent of integration between stock markets during stressful periods using the concept of copulas. Our methodology consists of fitting copulas to simultaneous exceedances of high thresholds, and computing copula‐based measures of interdependence and contagion. Using 21 pairs of emerging stock markets daily returns, we investigate if dependence increases with crisis, and analyse the chances of both markets crashing together. Dependence at joint positive and negative extreme returns levels may differ. This type of asymmetry is captured by the upper and lower tail dependence coefficients. Propagation of crisis may be faster in one direction, and this feature is captured by asymmetric copulas. Copyright © 2005 John Wiley &amp; Sons, Ltd.

Acute alteration of emotional behaviour in epileptic seizures is related to transient desynchrony in emotion-regulation networks

Objective During focal epileptic seizures, patients may express intense agitation, screaming and facial expressions of rage, fear or anger. The precise anatomical origin of such intense ictal emotional behaviour is not fully understood and the mechanisms by which the epileptic discharges provoke these phenomena are unknown. In the present study, we analysed the neurophysiological mechanisms underlying ictal emotional behaviour in 3 patients with frontal lobe epilepsies undergoing intracerebral recordings for presurgical evaluation. Methods We analyzed the interactions between regions forming ‘emotional networks’, before and during behavioural alterations. Intracerebral recordings (SEEG method) of seizures from 3 patients presenting with frontal lobe seizures were analyzed. A nonlinear measure of SEEG signal interdependencies was used to evaluate the functional couplings occurring between brain structures. Results We found that these intense emotional alterations were associated with a decrease of synchrony between signals recorded from the neural networks known to be involved in emotional processing, and in particular a loss of synchrony between the orbito-frontal cortex and the amygdala. This disruption of functional connections could then result in the disruption of emotional regulation leading to the release of altered behaviour, as observed in epileptic patients during seizures. Conclusions We propose that the occurrence of intense ictal emotional behaviour disturbance in frontal lobe seizures is related to a disruption of the normal mechanisms of emotional regulation Significance These results provide some insight into our understanding of the pathophysiological processes involved in human partial epilepsies as well as in the interpretation of clinical semiology.

EEG responses to long-term audio–visual stimulation

In this study, linear and nonlinear electroencephalogram (EEG) changes due to long-term audio–visual stimulation (AVS) were investigated. In the course of 2 months, 25 repetitions of a 20-min AVS program with stimulation frequencies in the range 2–18 Hz were applied to six healthy volunteers. EEG data were recorded from six head locations during relaxed wakefulness prior to AVS. Then linear spectral measures (total power, frequency band powers, spectral edge frequency, and spectral entropy), nonlinear measures of complexity (histogram-based entropy and correlation dimension), interdependency measures (linear correlation coefficient, mutual information, and coherence), and measures of subjective assessment were estimated. Evolution of these measures during the whole experiment period was analyzed with respect to the significance of their linear regression. Our results confirm that repetitive training with audio–visual stimulation does induce changes in the electro-cortical activity of the brain. Long-term AVS significantly increased power in theta-1, theta-2, and alpha-1 bands in the frontal and central cortex locations. Total power increased in the right central region. Interhemispheric coherence in alpha-1 band displayed a significant increase between frontal parts in contrast to the decrease of both linear correlation and mutual information. Correlation dimension significantly decreased in some locations while entropy displayed an ascending trend.

Entorhinal Cortex Involvement in Human Mesial Temporal Lobe Epilepsy: An Electrophysiologic and Volumetric Study

Several studies have demonstrated diminution in the volume of entorhinal cortex (EC) ipsilateral to the pathologic side in patients with temporal lobe epilepsy (TLE). The relation between the degree of EC atrophy and the epileptogenicity of this structure has never been directly studied. The purpose of the study was to determine whether atrophy of the EC evaluated by the quantitative magnetic resonance imaging (MRI) method is correlated with the epileptogenicity of this structure in TLE. Intracerebral recordings (SEEG method) of seizures from 11 patients with mesial TLE were analyzed. Seizures were classified according to patterns of onset: pattern 1 was the emergence of a low-frequency, high-amplitude rhythmic spiking followed by a tonic discharge, and pattern 2 was the emergence of a tonic discharge in the mesial structures. A nonlinear measure of SEEG signal interdependencies was used to evaluate the functional couplings occurring between hippocampus (Hip) and EC at seizure onset. MRI volumetric analysis was performed by using a T(1)-weighted three-dimensional gradient-echo sequence in TLE patients and 12 healthy subjects. Significant interactions between Hip and Ec were quantified at seizure onset. The EC was found to be the leader structure in most of the pattern 2 seizures. Volumetric measurements of EC demonstrated an atrophy in 63% of patients ipsilateral to the epileptic side. A significant correlation between the strength of EC-Hip coupling and the degree of atrophy was found. In addition, in those patients that had a normal EC volume, the EC was never the leader structure in Ec-Hip coupling. These results validate the potential role of volumetry to predict the epileptogenesis of the EC in patients with hippocampal sclerosis and MTLE.

Three measures of closeness in adolescents’ relationships with parents and friends: Variations and developmental significance

AbstractTwo studies examined the nature and developmental significance of closeness in adolescents’ relationships with parents and friends. Three measures of relationship closeness (i.e., interdependence, emotional tone, and subjective opinion) were compared and contrasted. In Study 1, grade and gender differences in closeness in relationships with mothers, fathers, and friends were examined. Participants were 133 adolescents in Grades 7, 9, and 11 and 135 of their parents. Closeness in relationships with mothers, fathers, and friends varied based on closeness measure, grade of adolescent, gender of adolescent, and gender of parent. The results suggest that the interdependence measure offers a perspective on adolescents’ close relationships that differs from that provided by the emotional tone and subjective opinion measures. In Study 2, associations were examined between the three measures of closeness in adolescents’ relationships with mothers, fathers, and friends and adolescents’ problem behavior, substance use, and school performance. Participants included 107 adolescents in Grades 7 and 10. In combination, the measures of closeness in relationships with mothers and with fathers explained significant variability in the criterion variables, and reports of interdependence and emotional tone emerged as unique, significant predictors. The results highlight distinctions among the three conceptualizations that are commonly purported to assess a close relationship and point to the utility and validity of interdependence and emotional tone as measures of closeness in adolescents’ relationships.

Inter-role Relationships in Hospital-based Pharmacy and Therapeutics Committee Decision Making

The interdependencies of Pharmacy and Therapeutics Committee members in 222 teaching hospitals were studied by use of the social relations model. Cooperation, influence, frustration and enjoyment were studied among four-person subgroups chosen from the five roles recommended for hospitals by the American Society of Hospital Pharmacists: physician-chair, physician-nonchair, pharmacist, nurse and administrator. The results show that the elicitation and reception of cooperation, influence, frustration and enjoyment vary considerably by role (as manifest in actor and partner effects); small amounts of individual reciprocity (i.e. the association between actor and partner effects) were found for some measures of interdependence across roles, while small amounts of dyadic reciprocity (i.e. the association between reciprocal relationship effects) were found for many relationships. Significant group level (i.e. committee) effects were found as well.

Uncertainty of the Liberal Peace

Variable selection is a crucial aspect of formulating a model to empirically examine data, as omitted variables can create spurious association, while inclusion of irrelevant variables can bias the results of one’s estimates. To mitigate such problems, researchers rely on theory to guide their selection of variables to include in their models. Unfortunately, in social science, there often exist several plausible theories to explain actions, and hence several models that researchers can use in their empirical work. This lack of unique theory is evident in examining trade’s effect on conflict, as there are three main theories on this and each suggests a different effect for trade interdependence on conflict. Empirically, the effect of trade on conflict remains uncertain, as researchers Barbieri and Oneal &amp; Russett have come to disparate conclusions using different measures of trade interdependence (models). Each of their inferences is based on the belief that the variables they select form the ‘true’ model that generates the data. The problem is that theory is unable to indicate whether one model is more appropriate than another, which creates uncertainty over the empirical effects of trade on conflict. To account for uncertainty in model selection, the author allows for several models by applying Bayesian model averaging (BMA) to the study of conflict. Accounting for this uncertainty, he finds that trade interdependence does not have a significant effect on the prediction of militarized conflict, whereas joint democracy continues to reduce conflict.

When in Peril, Retrench: Testing the Portfolio Channel of Contagion

One plausible mechanism through which financial market shocks may propagate across countries is through the impact that past gains and losses may have on investors' risk aversion and behavior. This paper presents a stylized model illustrating how heterogeneous changes in investors' risk aversion affect portfolio allocation decisions and stock prices. Our empirical findings suggest that when funds' returns are below average, they adjust their holdings toward the average (or benchmark) portfolio. In so doing, funds tend to sell the assets of countries in which they were overweight", increasing their exposure to countries in which they were "underweight." Based on this insight, the paper constructs an index of "financial interdependence" which reflects the extent to which countries share overexposed funds. The index helps in explain the pattern of stock market comovement across countries. Moreover, a comparison of this interdependence measure to indices of trade or commercial bank linkages indicates that our index can improve predictions about which countries are more likely to be affected by contagion from crisis centers.

Robust measure for characterizing generalized synchronization.

Generalized synchronization between two coupled systems can be characterized by recently proposed interdependency measures calculated from two simultaneously observed time series from them. However, numerical tests have shown that these measures cannot consistently indicate the direction of the coupling for strongly coupled systems or in situations with a large phase space neighbor size. An interdependency measure is proposed here quantifying how close a conditional neighbor is to a true neighbor in terms of the degree of alignment of their principal axes. Numerical tests are carried out on time series generated from a coupled Hénon map and a Lorenz model driven by a Rossler model. Given that a driving system is more dependent on a response system, the results show that the direction of the coupling is consistently detected by using the proposed measure even in those unfavorable cases for the measures mentioned above.