Multi-source Conditions Research Articles

Modulation of movement-related oscillatory signatures by cognitive interference in healthy aging.

Age-related changes in the neurophysiology underlying motor control are well documented, but whether these changes are specific to motor function or more broadly reflect age-related alterations in fronto-parietal circuitry serving attention and other higher-level processes remains unknown. Herein, we collected high-density magnetoencephalography (MEG) in 72 healthy adults (age 28-63years) as they completed an adapted version of the multi-source interference task that involved two subtypes of cognitive interference (i.e., flanker and Simon) and their integration (i.e., multi-source). All MEG data were examined for age-related changes in neural oscillatory activity using a whole-brain beamforming approach. Our primary findings indicated robust behavioral differences in task performance based on the type of interference, as well as stronger beta oscillations with increasing age in the right dorsolateral prefrontal cortices (flanker and multi-source conditions), left parietal (flanker and Simon), and medial parietal regions (multi-source). Overall, these data indicate that healthy aging is associated with alterations in higher-order association cortices that are critical for attention and motor control in the context of cognitive interference.

Robust and Efficient DOA-Steered Adaptive MVDR-FROST Beamforming Model for Multi-source Low SNR Environment

In the last few years, the demand of robust beamforming techniques has been increased significantly to serve numerous purposes. However, beamforming under low Signal to Noise Ratio (SNR) condition has always been a challenging task, which becomes more tedious in case of multiple sources. On the other hand, there are numerous factors such as steering vector error or similar estimation error problems that confine the efficiency of major beamforming techniques. Classical methods employ Eigen-Value Decomposition (EVD) and Singular Value Decomposition (SVD) over covariance matrix of the received signal; however their efficiency is limited under low SNR and multi-source condition, and perform inferiorly in case of steering vector errors. Such approaches are limited to achieve optimal Direction-of-Arrival (DOA) estimation that degrades the overall performance of the beamformer. Considering all these limitations, in this research, the focus is made on designing a robust DOA estimation model, followed by a novel beamformer for 8-element Uniform Linear Array (ULA). The simulation work consists two parts DOA estimation and beamforming. Unlike classical MUSIC and ESPRIT algorithms popular for DOA estimation our proposed model exploits the propagation method based subspace method where at first covariance matrix is obtained for the received signal, which is followed by normalization and Cross-Correlation matrix estimation. The obtained correlation matrix is processed for Generalized Eigen-Value Decomposition (GEVD) that efficiently obtained (orthogonal) subspace and SOI separation to yield DOA information. This approach enables more efficient DOA estimation even under low-SNR and steering vector error conditions. After obtaining DOA information, a novel adaptive beamformer is designed by using MVDR and FROST in parallel. DOA information from proposed model is given as input to the adaptive MVDR FROST beamforming model. Exploiting dynamic Signal-to-Interference ratio (SINR) by each beamformer our proposed method introduces an adaptation model that intends to achieve higher SINR value. MATLAB 2018a based simulation confirmed the robustness of the proposed model in terms of DOA estimation and beamforming results.

Approach of measuring PoC of context using limited self‐feedback in context‐aware systems

In context-aware systems (CASs), due to various reasons such as faulty sensors, the context information received from a context provider does not always represent accurately the reality, and incorrect contexts often lead to conflicts in multi-source conditions. The need of accurate data fusion results in research on the parameter — probability of correctness (PoC), which denotes the probability that a piece of information is correct. This study focuses on precise evaluation of PoC and utilises this parameter to accomplish more accurate data fusion ultimately. The authors propose a novel approach based on limited self-feedback by taking the output of data fusion process as criterion to evaluate PoC automatically and dynamically. Supervisory mechanism is used to ensure the credibility of self-feedback data. The updated PoC will affect the accuracy of the following rounds of data fusion based on Dempster–Shafer (DS) theory. Experiments testify from multiple perspectives that compared with the traditional user feedback-based method, this self-assessment-based approach can achieve more precise evaluation of PoC with less human interaction and effectively improve the accuracy of data fusion through PoC-based DS theory. Thus, the information or services provided by CASs will be more accurate and efficient.

Phonotactic walking paths of field crickets in closed-loop conditions and their simulation using a stochastic model

Field cricket females localize one of many singing males in the field in closed-loop multi-source conditions. To understand this behaviour, field cricket phonotaxis was investigated in a closed-loop walking phonotaxis paradigm, in response to two simultaneously active speakers playing aphasic calling songs. Female phonotactic paths were oriented towards the louder sound sources, but showed great inter-individual variability. Decisions made in the initial phases were correlated with the overall directions of the paths. Interestingly, the sound pressure levels of stimuli did not greatly influence several features of phonotactic paths such as sinuosity, walking bout lengths and durations. In order to ascertain the extent of our understanding of walking phonotaxis, a stochastic model was used to simulate the behaviour observed in the experiment. The model incorporated data from the experiment and our current understanding of field cricket auditory physiology. This model, based on stochastic turning towards the louder side, successfully recaptured several qualitative and quantitative features of the observed phonotactic paths. The simulation also reproduced the paths observed in a separate outdoor field experiment. Virtual crickets that were unilaterally deafened or had poor ear directionality exhibited walking paths similar to those observed in previous experiments.