## White Noise

14,000,000 Leading Edge Experts on the ideXlab platform

## Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 95748 Experts worldwide ranked by ideXlab platform

### Elaine Schepers - One of the best experts on this subject based on the ideXlab platform.

• ##### White Noise speech illusions a trait dependent risk marker for psychotic disorder
Frontiers in Psychiatry, 2019
Co-Authors: Elaine Schepers, Sinan Guloksuz, Philippe Delespaul, Richel Lousberg, Lottakatrin Pries, Gunter Kenis, Jurjen J Luykx, Bochao D Lin, Alexander Richards, Berna Binnur Akdede
Abstract:

Introduction: White Noise speech illusions index liability for psychotic disorder in case-control comparisons. In the current study, we examined i) the rate of White Noise speech illusions in siblings of patients with psychotic disorder, and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder (psychotic experiences assessed with the CAPE scale and cognitive ability). Methods: The White Noise task was used as an experimental paradigm to elicit and measure speech illusions in 1014 patients with psychotic disorders, 1157 siblings and 1507 healthy participants. We examined associations between speech illusions and increasing familial risk (control -> sibling -> patient), modelled both as a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between White Noise speech illusions across hypothesized increasing levels of familial risk (controls -> siblings -> patients): OR linear 1.11, 95% CI 1.02-1.21, p =0.019), there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79-1.09, p =0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction =0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85-1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09-1.46) , cognitive ability was lower (p interaction <0.001; ORhigh cognitive ability= 0.94, 95% CI 0.84-1.05; ORlow cognitive ability= 1.43, 95% CI 1.23-1.68) and exposure to childhood adversity was higher (p interaction <0.001; ORlow adversity 0.92, 95% CI 0.82-1.04; ORhigh adversity 1.31, 95% CI 1.13-1.52). A similar, although less marked, pattern was seen for categorical patient-control and sibling-control comparisons. Exposure to recent life events did not modify the association between White Noise and familial risk (p interaction=0.232). Conclusion: The association between White Noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.

• ##### White Noise speech illusions a trait dependent risk marker for psychotic disorder
Frontiers in Psychiatry, 2019
Co-Authors: Elaine Schepers, Sinan Guloksuz, Philippe Delespaul, Richel Lousberg, Lottakatrin Pries, Gunter Kenis, Jurjen J Luykx, Bochao D Lin, Alexander Richards, Berna Binnur Akdede
Abstract:

Introduction: White Noise speech illusions index liability for psychotic disorder in case– control comparisons. In the current study, we examined i) the rate of White Noise speech illusions in siblings of patients with psychotic disorder and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder [psychotic experiences assessed with the Community Assessment of Psychic Experiences (CAPE) scale and cognitive ability]. Methods: The White Noise task was used as an experimental paradigm to elicit and measure speech illusions in 1,014 patients with psychotic disorders, 1,157 siblings, and 1,507 healthy participants. We examined associations between speech illusions and increasing familial risk (control-> sibling-> patient), modeled as both a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between White Noise speech illusions across hypothesized increasing levels of familial risk (controls-> siblings-> patients) [odds ratio (OR) linear 1.11, 95% confidence interval (CI) 1.02–1.21, p = 0.019], there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79–1.09, p = 0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction = 0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85–1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09–1.46); cognitive ability was lower (p interaction < 0.001; ORhigh cognitive ability 0.94, 95% CI 0.84–1.05; ORlow cognitive ability 1.43, 95% CI 1.23–1.68); and exposure to childhood adversity was higher (p interaction < 0.001; ORlow adversity 0.92, 95% CI 0.82–1.04; ORhigh adversity 1.31, 95% CI 1.13–1.52). A similar, although less marked, pattern was seen for categorical patient– control and sibling–control comparisons. Exposure to recent life events did not modify the association between White Noise and familial risk (p interaction = 0.232). Conclusion: The association between White Noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure to childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.

• ##### White Noise speech illusions in the general population the association with psychosis expression and risk factors for psychosis
PLOS ONE, 2019
Co-Authors: Elaine Schepers, Richel Lousberg
Abstract:

INTRODUCTION: Positive psychotic experiences are associated with increased rate of White Noise speech illusions in patients and their relatives. However, findings have been conflicting to what degree speech illusions are associated with subclinical expression of psychosis in the general population. The aim of this study was to investigate the link between speech illusions and positive psychotic experiences in a general population sample. In addition, the hypothesis that speech illusions are on the pathway from known risk factors for psychosis (childhood adversity and recent life events) to subthreshold expression of psychosis, was examined. METHODS: In a follow-up design (baseline and 6 months) the association between the number of White Noise speech illusions and self-reported psychotic experiences, assessed with the Community Assessment of Psychic Experiences (CAPE), was investigated in a general population sample (n = 112). In addition, associations between speech illusions and childhood adversity and life events, using the Childhood Experiences of Care and Abuse questionnaire and the Social Readjustment Rating Scale, were investigated. RESULTS: No association was found between the CAPE positive scale and the number of White Noise speech illusions. The CAPE positive scale was significantly associated with childhood adversity between 12 and 16 years (B = 0.980 p = 0.001) and life events (B = 0.488 p = 0.044). The number of speech illusions showed no association with either life events or childhood adversity. CONCLUSION: In the nonclinical population, the pathway from risk factors to expression of subclinical psychotic experiences does not involve White Noise speech illusions as an intermediate outcome.

### Berna Binnur Akdede - One of the best experts on this subject based on the ideXlab platform.

• ##### White Noise speech illusions a trait dependent risk marker for psychotic disorder
Frontiers in Psychiatry, 2019
Co-Authors: Elaine Schepers, Sinan Guloksuz, Philippe Delespaul, Richel Lousberg, Lottakatrin Pries, Gunter Kenis, Jurjen J Luykx, Bochao D Lin, Alexander Richards, Berna Binnur Akdede
Abstract:

Introduction: White Noise speech illusions index liability for psychotic disorder in case-control comparisons. In the current study, we examined i) the rate of White Noise speech illusions in siblings of patients with psychotic disorder, and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder (psychotic experiences assessed with the CAPE scale and cognitive ability). Methods: The White Noise task was used as an experimental paradigm to elicit and measure speech illusions in 1014 patients with psychotic disorders, 1157 siblings and 1507 healthy participants. We examined associations between speech illusions and increasing familial risk (control -> sibling -> patient), modelled both as a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between White Noise speech illusions across hypothesized increasing levels of familial risk (controls -> siblings -> patients): OR linear 1.11, 95% CI 1.02-1.21, p =0.019), there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79-1.09, p =0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction =0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85-1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09-1.46) , cognitive ability was lower (p interaction <0.001; ORhigh cognitive ability= 0.94, 95% CI 0.84-1.05; ORlow cognitive ability= 1.43, 95% CI 1.23-1.68) and exposure to childhood adversity was higher (p interaction <0.001; ORlow adversity 0.92, 95% CI 0.82-1.04; ORhigh adversity 1.31, 95% CI 1.13-1.52). A similar, although less marked, pattern was seen for categorical patient-control and sibling-control comparisons. Exposure to recent life events did not modify the association between White Noise and familial risk (p interaction=0.232). Conclusion: The association between White Noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.

• ##### White Noise speech illusions a trait dependent risk marker for psychotic disorder
Frontiers in Psychiatry, 2019
Co-Authors: Elaine Schepers, Sinan Guloksuz, Philippe Delespaul, Richel Lousberg, Lottakatrin Pries, Gunter Kenis, Jurjen J Luykx, Bochao D Lin, Alexander Richards, Berna Binnur Akdede
Abstract:

Introduction: White Noise speech illusions index liability for psychotic disorder in case– control comparisons. In the current study, we examined i) the rate of White Noise speech illusions in siblings of patients with psychotic disorder and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder [psychotic experiences assessed with the Community Assessment of Psychic Experiences (CAPE) scale and cognitive ability]. Methods: The White Noise task was used as an experimental paradigm to elicit and measure speech illusions in 1,014 patients with psychotic disorders, 1,157 siblings, and 1,507 healthy participants. We examined associations between speech illusions and increasing familial risk (control-> sibling-> patient), modeled as both a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between White Noise speech illusions across hypothesized increasing levels of familial risk (controls-> siblings-> patients) [odds ratio (OR) linear 1.11, 95% confidence interval (CI) 1.02–1.21, p = 0.019], there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79–1.09, p = 0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction = 0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85–1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09–1.46); cognitive ability was lower (p interaction < 0.001; ORhigh cognitive ability 0.94, 95% CI 0.84–1.05; ORlow cognitive ability 1.43, 95% CI 1.23–1.68); and exposure to childhood adversity was higher (p interaction < 0.001; ORlow adversity 0.92, 95% CI 0.82–1.04; ORhigh adversity 1.31, 95% CI 1.13–1.52). A similar, although less marked, pattern was seen for categorical patient– control and sibling–control comparisons. Exposure to recent life events did not modify the association between White Noise and familial risk (p interaction = 0.232). Conclusion: The association between White Noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure to childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.

### Richel Lousberg - One of the best experts on this subject based on the ideXlab platform.

• ##### White Noise speech illusions a trait dependent risk marker for psychotic disorder
Frontiers in Psychiatry, 2019
Co-Authors: Elaine Schepers, Sinan Guloksuz, Philippe Delespaul, Richel Lousberg, Lottakatrin Pries, Gunter Kenis, Jurjen J Luykx, Bochao D Lin, Alexander Richards, Berna Binnur Akdede
Abstract:

Introduction: White Noise speech illusions index liability for psychotic disorder in case-control comparisons. In the current study, we examined i) the rate of White Noise speech illusions in siblings of patients with psychotic disorder, and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder (psychotic experiences assessed with the CAPE scale and cognitive ability). Methods: The White Noise task was used as an experimental paradigm to elicit and measure speech illusions in 1014 patients with psychotic disorders, 1157 siblings and 1507 healthy participants. We examined associations between speech illusions and increasing familial risk (control -> sibling -> patient), modelled both as a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between White Noise speech illusions across hypothesized increasing levels of familial risk (controls -> siblings -> patients): OR linear 1.11, 95% CI 1.02-1.21, p =0.019), there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79-1.09, p =0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction =0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85-1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09-1.46) , cognitive ability was lower (p interaction <0.001; ORhigh cognitive ability= 0.94, 95% CI 0.84-1.05; ORlow cognitive ability= 1.43, 95% CI 1.23-1.68) and exposure to childhood adversity was higher (p interaction <0.001; ORlow adversity 0.92, 95% CI 0.82-1.04; ORhigh adversity 1.31, 95% CI 1.13-1.52). A similar, although less marked, pattern was seen for categorical patient-control and sibling-control comparisons. Exposure to recent life events did not modify the association between White Noise and familial risk (p interaction=0.232). Conclusion: The association between White Noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.

• ##### White Noise speech illusions a trait dependent risk marker for psychotic disorder
Frontiers in Psychiatry, 2019
Co-Authors: Elaine Schepers, Sinan Guloksuz, Philippe Delespaul, Richel Lousberg, Lottakatrin Pries, Gunter Kenis, Jurjen J Luykx, Bochao D Lin, Alexander Richards, Berna Binnur Akdede
Abstract:

Introduction: White Noise speech illusions index liability for psychotic disorder in case– control comparisons. In the current study, we examined i) the rate of White Noise speech illusions in siblings of patients with psychotic disorder and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder [psychotic experiences assessed with the Community Assessment of Psychic Experiences (CAPE) scale and cognitive ability]. Methods: The White Noise task was used as an experimental paradigm to elicit and measure speech illusions in 1,014 patients with psychotic disorders, 1,157 siblings, and 1,507 healthy participants. We examined associations between speech illusions and increasing familial risk (control-> sibling-> patient), modeled as both a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between White Noise speech illusions across hypothesized increasing levels of familial risk (controls-> siblings-> patients) [odds ratio (OR) linear 1.11, 95% confidence interval (CI) 1.02–1.21, p = 0.019], there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79–1.09, p = 0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction = 0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85–1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09–1.46); cognitive ability was lower (p interaction < 0.001; ORhigh cognitive ability 0.94, 95% CI 0.84–1.05; ORlow cognitive ability 1.43, 95% CI 1.23–1.68); and exposure to childhood adversity was higher (p interaction < 0.001; ORlow adversity 0.92, 95% CI 0.82–1.04; ORhigh adversity 1.31, 95% CI 1.13–1.52). A similar, although less marked, pattern was seen for categorical patient– control and sibling–control comparisons. Exposure to recent life events did not modify the association between White Noise and familial risk (p interaction = 0.232). Conclusion: The association between White Noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure to childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.

• ##### White Noise speech illusions in the general population the association with psychosis expression and risk factors for psychosis
PLOS ONE, 2019
Co-Authors: Elaine Schepers, Richel Lousberg
Abstract:

INTRODUCTION: Positive psychotic experiences are associated with increased rate of White Noise speech illusions in patients and their relatives. However, findings have been conflicting to what degree speech illusions are associated with subclinical expression of psychosis in the general population. The aim of this study was to investigate the link between speech illusions and positive psychotic experiences in a general population sample. In addition, the hypothesis that speech illusions are on the pathway from known risk factors for psychosis (childhood adversity and recent life events) to subthreshold expression of psychosis, was examined. METHODS: In a follow-up design (baseline and 6 months) the association between the number of White Noise speech illusions and self-reported psychotic experiences, assessed with the Community Assessment of Psychic Experiences (CAPE), was investigated in a general population sample (n = 112). In addition, associations between speech illusions and childhood adversity and life events, using the Childhood Experiences of Care and Abuse questionnaire and the Social Readjustment Rating Scale, were investigated. RESULTS: No association was found between the CAPE positive scale and the number of White Noise speech illusions. The CAPE positive scale was significantly associated with childhood adversity between 12 and 16 years (B = 0.980 p = 0.001) and life events (B = 0.488 p = 0.044). The number of speech illusions showed no association with either life events or childhood adversity. CONCLUSION: In the nonclinical population, the pathway from risk factors to expression of subclinical psychotic experiences does not involve White Noise speech illusions as an intermediate outcome.

### Shuli Sun - One of the best experts on this subject based on the ideXlab platform.

• ##### multisensor optimal information fusion input White Noise deconvolution estimators
Systems Man and Cybernetics, 2004
Co-Authors: Shuli Sun
Abstract:

The unified multisensor optimal information fusion criterion weighted by matrices is rederived in the linear minimum variance sense, where the assumption of normal distribution is avoided. Based on this fusion criterion, the optimal information fusion input White Noise deconvolution estimators are presented for discrete time-varying linear stochastic control system with multiple sensors and correlated Noises, which can be applied to seismic data processing in oil exploration. A three-layer fusion structure with fault tolerant property and reliability is given. The first fusion layer and the second fusion layer both have netted parallel structures to determine the first-step prediction error cross-covariance for the state and the estimation error cross-covariance for the input White Noise between any two sensors at each time step, respectively. The third fusion layer is the fusion center to determine the optimal matrix weights and obtain the optimal fusion input White Noise estimators. The simulation results for Bernoulli-Gaussian input White Noise deconvolution estimators show the effectiveness.

• ##### technical communique multi sensor information fusion White Noise filter weighted by scalars based on kalman predictor
Automatica, 2004
Co-Authors: Shuli Sun
Abstract:

A unified multi-sensor optimal information fusion criterion weighted by scalars is presented in the linear minimum variance sense. The criterion considers the correlation among local estimation errors, only requires the computation of scalar weights, and avoids the computation of matrix weights so that the computational burden can obviously be reduced. Based on this fusion criterion and Kalman predictor, an optimal information fusion filter for the input White Noise, which can be applied to seismic data processing in oil exploration, is given for discrete time-varying linear stochastic control systems measured by multiple sensors with correlated Noises. It has a two-layer fusion structure. The first fusion layer has a netted parallel structure to determine the first-step prediction error cross-covariance for the state and the filtering error cross-covariance for the input White Noise between any two sensors at each time step. The second fusion layer is the fusion center to determine the optimal scalar weights and obtain the optimal fusion filter for the input White Noise. Two simulation examples for Bernoulli-Gaussian White Noise filter show the effectiveness.

### Kolyan Ray - One of the best experts on this subject based on the ideXlab platform.

• ##### adaptive bernstein von mises theorems in gaussian White Noise
Annals of Statistics, 2017
Co-Authors: Kolyan Ray
Abstract:

We investigate Bernstein–von Mises theorems for adaptive nonparametric Bayesian procedures in the canonical Gaussian White Noise model. We consider both a Hilbert space and multiscale setting with applications in $L^{2}$ and $L^{\infty}$, respectively. This provides a theoretical justification for plug-in procedures, for example the use of certain credible sets for sufficiently smooth linear functionals. We use this general approach to construct optimal frequentist confidence sets based on the posterior distribution. We also provide simulations to numerically illustrate our approach and obtain a visual representation of the geometries involved.