Search results for " network"
showing 10 items of 6428 documents
LOW-RANK APPROXIMATION BASED NON-NEGATIVE MULTI-WAY ARRAY DECOMPOSITION ON EVENT-RELATED POTENTIALS
2014
Non-negative tensor factorization (NTF) has been successfully applied to analyze event-related potentials (ERPs), and shown superiority in terms of capturing multi-domain features. However, the time-frequency representation of ERPs by higher-order tensors are usually large-scale, which prevents the popularity of most tensor factorization algorithms. To overcome this issue, we introduce a non-negative canonical polyadic decomposition (NCPD) based on low-rank approximation (LRA) and hierarchical alternating least square (HALS) techniques. We applied NCPD (LRAHALS and benchmark HALS) and CPD to extract multi-domain features of a visual ERP. The features and components extracted by LRAHALS NCP…
Multi-domain feature extraction for small event-related potentials through nonnegative multi-way array decomposition from low dense array EEG
2013
Non-negative Canonical Polyadic decomposition (NCPD) and non-negative Tucker decomposition (NTD) were compared for extracting the multi-domain feature of visual mismatch negativity (vMMN), a small event-related potential (ERP), for the cognitive research. Since signal-to-noise ratio in vMMN is low, NTD outperformed NCPD. Moreover, we proposed an approach to select the multi-domain feature of an ERP among all extracted features and discussed determination of numbers of extracted components in NCPD and NTD regarding the ERP context.
Permanently online and permanently connected : development and validation of the Online Vigilance Scale
2017
Smartphones and other mobile devices have fundamentally changed patterns of Internet use in everyday life by making online access constantly available. The present paper offers a theoretical explication and empirical assessment of the concept of online vigilance, referring to users' permanent cognitive orientation towards online content and communication as well as their disposition to exploit these options constantly. Based on four studies, a validated and reliable self-report measure of online vigilance was developed. In combination, the results suggest that the Online Vigilance Scale (OVS) shows a stable factor structure in various contexts and user populations and provides future work i…
pBrain: A novel pipeline for Parkinson related brain structure segmentation
2020
[EN] Parkinson is a very prevalent neurodegenerative disease impacting the life of millions of people worldwide. Although its cause remains unknown, its functional and structural analysis is fundamental to advance in the search of a cure or symptomatic treatment. The automatic segmentation of deep brain structures related to Parkinson's disease could be beneficial for the follow up and treatment planning. Unfortunately, there is not broadly available segmentation software to automatically measure Parkinson related structures. In this paper, we present a novel pipeline to segment three deep brain structures related to Parkinson's disease (substantia nigra, subthalamic nucleus and red nucleus…
Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures
2001
In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of …
Task-induced deactivation in diverse brain systems correlates with interindividual differences in distinct autonomic indices
2018
AbstractNeuroimaging research has shown that different cognitive tasks induce relatively specific activation patterns, as well as less task-specific deactivation patterns. Here we examined whether individual differences in Autonomic Nervous System (ANS) activity during task performance correlate with the magnitude of task-induced deactivation. In an fMRI study, participants performed a continuous mental arithmetic task in a task/rest block design, while undergoing combined fMRI and heart / respiration rate acquisitions using photoplethysmograph and respiration belt. As expected, task performance increased heart-rate and reduced the RMSSD, a cardiac index related to vagal tone. Across partic…
Money, Social Relationships and the Sense of Self: The Consequences of an Improved Financial Situation for Persons Suffering from Serious Mental Illn…
2017
During a 9-month period, 100 persons with SMI were given approx. 73 USD per month above their normal income. Sixteen of the subjects were interviewed. The interviews were analysed according to the methods of thematic analysis. The money was used for personal pleasure and to re-establish reciprocal relations to others. The ways in which different individuals used the money at their disposal impacted their sense of self through experiences of mastery, agency, reciprocity, recognition and security. The findings underline the importance of including social circumstances in our understanding of mental health problems, their trajectories and the recovery process.
The facilitative effect of gestures on the neural processing of semantic complexity in a continuous narrative
2019
© 2019 Elsevier Inc. Gestures are elemental components of social communication and aid comprehension of verbal messages; however, little is known about the potential role of gestures in facilitating processing of semantic complexity in an ecologically valid setting. The goal of this study was to investigate whether cognitive load, as indexed by semantic complexity, is modulated by the presentation of gestures accompanying speech. Twenty healthy participants watched 16 video clips of a short narrative while instructed to carefully listen to and watch the narrator while functional magnetic resonance imaging (fMRI) data were acquired. The videos contained passages with and without various co-s…
Epoch versus impulse models in the analysis of parametric fMRI studies
2013
Abstract Objective In parametric fMRI studies the relationship between the amplitude of the hemodynamic response and electrophysiological or behavioral parameters is commonly analyzed using the general linear model (GLM). We examined ways of using single-trial response time (RT) in the analysis of a decision-making task to better isolate task-specific activation. Methods fMRI and RT data were recorded in twenty-one subjects performing a visual-oddball-task. Four explanatory variables (EVs) were generated for the GLM-analysis: A conventional (constant impulse) EV, a constant epoch EV informed using subjects’ average RT, a variable impulse EV and a variable epoch EV both informed using single…
Discovering dynamic task-modulated functional networks with specific spectral modes using MEG.
2019
Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of MEG to m…