Neural Dynamics of Target Detection via Wireless EEG in Embodied Cognition

Abstract

Embodied cognitive attention detection is important for many real-world applications, such as monitoring attention in daily driving and studying. Exploring how the brain and behavior are influenced by visual sensory inputs becomes a major challenge in the real world. The neural activity of embodied mind cognitive states can be understood through simple symbol experimental design. However, searching for a particular target in the real world is more complicated than during a simple symbol experiment in the laboratory setting. Hence, the development of realistic situations for investigating the neural dynamics of subjects during real-world environments is critical. This study designed a novel military-inspired target detection task for investigating the neural activities of performing embodied cognition tasks in the real-world setting. We adopted independent component analysis (ICA) and electroencephalogram (EEG) dipole source localization methods to study the participant’s event-related potentials (ERPs), event-related spectral perturbation (ERSP), and power spectral density (PSD) during the target detection task using a wireless EEG system, which is more convenient for real-life use. Behavioral results showed that the response time in the congruent condition (582 ms) was shorter than those in the incongruent (666 ms) and nontarget (863 ms) conditions. Regarding the EEG observation, we observed N200-P300 wave activation in the middle occipital lobe and P300-N500 wave activation in the right frontal lobe and left motor cortex, which are associated with attention ERPs. Furthermore, delta (1–4 Hz) and theta (4–7 Hz) band powers in the right frontal lobe, as well as alpha (8–12 Hz) and beta (13–30 Hz) band powers in the left motor cortex were suppressed, whereas the theta (4–7 Hz) band powers in the middle occipital lobe were increased considerably in the attention task. Experimental results showed that the embodied body function influences human mental states and psychological performance under cognition attention tasks. These neural markers will be also feasible to implement in the real-time brain computer interface. Novel findings in this study can be helpful for humans to further understand the interaction between the brain and behavior in multiple target detection conditions in real life.

Auditory experience modulates fronto-parietal theta activity serving fluid intelligence

“…This visual theta response has been shown to be enhanced with increased attention to a visual stimulus. 48 Thus, CHH may have been using greater attentional resources than CNH during the initial processing of the complex stimulus presented in this task. It is possible that this increased attention reflects a greater need or it could indicate a more general mechanism by which CHH process their environment due to degraded auditory input.…”

Multi-Parameter Physiological State Monitoring in Target Detection Under Real-World Settings

“…In this study, we designed a target detection experiment that simulates a battlefield scenario to elicit state changes assessed by the proposed indicator ( He et al, 2021 ). The experiment was composed of a 30-s EEG baseline recording and five blocks of 12-min sessions along with a 5-min rest session.…”

“…The experiment was composed of five sessions and five resting periods, with each session consisting of 180 trials. Each subject was instructed to respond to the target, and the conditions of the stimulus referred to the relationship between the cue and the target ( He et al, 2021 ). To induce the effect of fatigue, the experiment lasted about 1 h.…”

Alternations in neural oscillation related to attention network reveal influence of indoor toluene on cognition at low concentration

“…Attention is the precondition of advanced cognitive functions composed of three functionally and anatomically distinct subsystems known as alerting network, orienting network, and executive network (EC) 32,33 . The attention network test (ANT) designed by Fan et al was used to evaluate the efficiency of three components of attention network, 34 and distinct brain oscillation pattern of the attention network has been found in previous research 35,36 …”