Kernel-based joint independence tests for multivariate stationary and non-stationary time series

Multivariate time-series data that capture the temporal evolution of interconnected systems are ubiquitous in diverse areas. Understanding the complex relationships and potential dependencies among co-observed variables is crucial for the accurate statistical modelling and analysis of such systems. Here, we introduce kernel-based statistical tests of joint independence in multivariate time series by extending the d-variable Hilbert-Schmidt independence criterion to encompass both stationary and non-stationary processes, thus allowing broader real-world applications. By leveraging resampling techniques tailored for both single- and multiple-realization time series, we show how the method robustly uncovers significant higher-order dependencies in synthetic examples, including frequency mixing data and logic gates, as well as real-world climate, neuroscience and socio-economic data. Our method adds to the mathematical toolbox for the analysis of multivariate time series and can aid in uncovering high-order interactions in data.

Information decomposition in the frequency domain: a new framework to study cardiovascular and cardiorespiratory oscillations

While cross-spectral and information-theoretic approaches are widely used for the multivariate analysis of physiological time series, their combined utilization is far less developed in the literature. This study introduces a framework for the spectral decomposition of multivariate information measures, which provides frequency-specific quantifications of the information shared between a target and two source time series and of its expansion into amounts related to how the sources contribute to the target dynamics with unique, redundant and synergistic information. The framework is illustrated in simulations of linearly interacting stochastic processes, showing how it allows us to retrieve amounts of information shared by the processes within specific frequency bands which are otherwise not detectable by time-domain information measures, as well as coupling features which are not detectable by spectral measures. Then, it is applied to the time series of heart period, systolic and diastolic arterial pressure and respiration variability measured in healthy subjects monitored in the resting supine position and during head-up tilt. We show that the spectral measures of unique, redundant and synergistic information shared by these variability series, integrated within specific frequency bands of physiological interest and reflect the mechanisms of short-term regulation of cardiovascular and cardiorespiratory oscillations and their alterations induced by the postural stress. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Model-based design for seizure control by stimulation

OBJECTIVE

Current brain stimulation paradigms are largely empirical rather than theoretical. An opportunity exists to improve upon their modest effectiveness in closed-loop control strategies with the development of theoretically grounded, model-based designs.

APPROACH

Inspired by this need, here we couple experimental data and mathematical modeling with a control-theoretic strategy for seizure termination. We begin by exercising a dynamical systems approach to model seizures (n = 94) recorded using intracranial EEG (iEEG) from 21 patients with medication-resistant, localization-related epilepsy.

MAIN RESULTS

Although each patient's seizures displayed unique spatial and temporal patterns, their evolution can be parsimoniously characterized by the same model form. Idiosyncracies of the model can inform individualized intervention strategies, specifically in iEEG samples with well-localized seizure onset zones. Temporal fluctuations in the spatial profiles of the oscillatory modes show that seizure onset marks a transition into a regime in which the underlying system supports prolonged rhythmic and focal activity. Based on these observations, we propose a control-theoretic strategy that aims to stabilize ictal activity using static output feedback for linear time-invariant switching systems. Finally, we demonstrate in silico that our proposed strategy allows us to dampen the emerging focal oscillatory sources using only a small set of electrodes.

SIGNIFICANCE

Our integrative study informs the development of modulation and control algorithms for neurostimulation that could improve the effectiveness of implantable, closed-loop anti-epileptic devices.

The impact of TV mass media campaigns on calls to a National Quitline and the use of prescribed nicotine replacement therapy: a structural vector autoregression analysis

AIMS

To estimate (1) the immediate impact; (2) the cumulative impact; and (3) the duration of impact of Scottish tobacco control TV mass media campaigns (MMCs) on smoking cessation activity, as measured by calls to Smokeline and the volume of prescribed nicotine replacement therapy (NRT).

DESIGN

Multivariate time-series analysis using secondary data on population level measures of exposure to TV MMCs broadcast and smoking cessation activity between 2003 and 2012.

SETTING AND PARTICIPANTS

Population of Scotland.

MEASUREMENTS

Adult television viewer ratings (TVRs) as a measure of exposure to Scottish mass media campaigns in the adult population; monthly calls to NHS Smokeline; and the monthly volume of prescribed NRT as measured by gross ingredient costs (GIC).

FINDINGS

Tobacco control TVRs were associated with an increase in calls to Smokeline but not an increase in the volume of prescribed NRT. A 1 standard deviation (SD) increase of 194 tobacco control TVRs led to an immediate and significant increase of 385.9 [95% confidence interval (CI) = 171.0, 600.7] calls to Smokeline (unadjusted model) within 1 month. When adjusted for seasonality the impact was reduced, but the increase in calls remained significant (226.3 calls, 95% CI = 37.3, 415.3). The cumulative impact on Smokeline calls remained significant for 6 months after broadcast in the unadjusted model and 18 months in the adjusted model. However, an increase in tobacco control TVRs of 194 failed to have a significant impact on the GIC of prescribed NRT in either the unadjusted (£1361.4, 95% CI = -£9138.0, £11860.9) or adjusted (£6297.1, 95% CI = -£2587.8, £15182.1) models.

CONCLUSIONS

Tobacco control television mass media campaigns broadcast in Scotland between 2003 and 2012 were effective in triggering calls to Smokeline, but did not increase significantly the use of prescribed nicotine replacement therapy by adult smokers. The impact on calls to Smokeline occurred immediately within 1 month of broadcast and was sustained for at least 6 months.

Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'.