Assessing Feedback Response With a Wearable Electroencephalography System

Social network structure modulates neural activities underlying group norm processing: evidence from event-related potentials

Introduction

Social ties play a crucial role in determining the health and wellbeing of individuals. However, it remains unclear whether the capacity to process social information distinguishes well-connected individuals from their less-connected peers. This study explored how an individual's social network structure influences the dynamic processing of group norms, utilizing event-related potentials (ERPs).

Methods

The study involved 43 university students from the same class who participated in a social network study measuring metrics such as real-life social network size, in-degree, out-degree, and betweenness centrality. Subsequently, 27 students participated in an EEG study assessing their willingness to engage in various exercises after being exposed to peer feedback or in its absence.

Results

The results indicate that an individual's social network structure is significantly associated with the dynamic processing of group norms. Notably, well-connected individuals exhibited larger ERP amplitudes linked to feedback (e.g., N200, P300, and LPP), greater functional segregation within the brain network (e.g., local efficiency and clustering coefficient), and enhanced synchronization within frontal area and across different brain areas.

Discussion

These findings highlight that well-connected individuals possess enhanced sensitivity and efficiency in processing social information, pointing to potential areas for further research on the factors influencing social network evolution.

Differences in cognitive processing between snakes and guns: Evidence from electroencephalography

The aim of the study is to explore differences in cognitive processing of phylogenetic and ontogenetic stimulus using the electroencephalography (EEG) technology. The researcher chose snakes and guns as representatives of phylogenetic stimulus and ontogenetic stimulus, respectively, and used the Oddball paradigm to present the experimental stimuli and explore the cognitive processing differences between them through time-domain analysis and time-frequency analysis. The results of time-domain analysis showed that snakes elicited larger N1, P2, and P3 amplitudes and a shorter P3 latency than guns and neutral stimuli, and that guns elicited greater P2 and P3 amplitudes than neutral stimuli. The findings of time-frequency analysis showed that the beta-band (320 - 420 ms, 25 - 35 Hz) power elicited by snakes was significantly greater than by guns and neutral stimuli, and that the beta-band power elicited by guns was significantly greater than by neutral stimuli. The results indicated that the brain has a cognitive processing advantage for both snakes and guns, which is more obvious for snakes than for guns, and that the brain is more sensitive to snakes.

Characterization of Retronasal Airflow Patterns during Intraoral Fluid Discrimination Using a Low-Cost, Open-Source Biosensing Platform

Nasal airflow plays a critical role in olfactory processes, and both retronasal and orthonasal olfaction involve sensorimotor processes that facilitate the delivery of volatiles to the olfactory epithelium during odor sampling. Although methods are readily available for monitoring nasal airflow characteristics in laboratory and clinical settings, our understanding of odor sampling behavior would be enhanced by the development of inexpensive wearable technologies. Thus, we developed a method of monitoring nasal air pressure using a lightweight, open-source brain-computer interface (BCI) system and used the system to characterize patterns of retronasal airflow in human participants performing an oral fluid discrimination task. Participants exhibited relatively sustained low-rate retronasal airflow during sampling punctuated by higher-rate pulses often associated with deglutition. Although characteristics of post-deglutitive pulses did not differ across fluid conditions, the cumulative duration, probability, and estimated volume of retronasal airflow were greater during discrimination of perceptually similar solutions. These findings demonstrate the utility of a consumer-grade BCI system in assessing human olfactory behavior. They suggest further that sensorimotor processes regulate retronasal airflow to optimize the delivery of volatiles to the olfactory epithelium and that discrimination of perceptually similar oral fluids may be accomplished by varying the duration of optimal airflow rate.

Age-Related Alterations in EEG Network Connectivity in Healthy Aging

Emerging studies have reported that functional brain networks change with increasing age. Graph theory is applied to understand the age-related differences in brain behavior and function, and functional connectivity between the regions is examined using electroencephalography (EEG). The effect of normal aging on functional networks and inter-regional synchronization during the working memory (WM) state is not well known. In this study, we applied graph theory to investigate the effect of aging on network topology in a resting state and during performing a visual WM task to classify aging EEG signals. We recorded EEGs from 20 healthy middle-aged and 20 healthy elderly subjects with their eyes open, eyes closed, and during a visual WM task. EEG signals were used to construct the functional network; nodes are represented by EEG electrodes; and edges denote the functional connectivity. Graph theory matrices including global efficiency, local efficiency, clustering coefficient, characteristic path length, node strength, node betweenness centrality, and assortativity were calculated to analyze the networks. We applied the three classifiers of K-nearest neighbor (KNN), a support vector machine (SVM), and random forest (RF) to classify both groups. The analyses showed the significantly reduced network topology features in the elderly group. Local efficiency, global efficiency, and clustering coefficient were significantly lower in the elderly group with the eyes-open, eyes-closed, and visual WM task states. KNN achieved its highest accuracy of 98.89% during the visual WM task and depicted better classification performance than other classifiers. Our analysis of functional network connectivity and topological characteristics can be used as an appropriate technique to explore normal age-related changes in the human brain.

Revisión de electroencefalografía portable y su aplicabilidad en neurociencias

La electroencefalografía (EEG) es una técnica que permite registrar la actividad eléctrica del cerebro y ha sido estudiada durante los últimos cien años en diferentes ámbitos de la neurociencia. En los últimos años se ha investigado y desarrollado equipos de medición que sean portables y que permitan una buena calidad de la señal, por lo cual se realizó una revisión bibliográfica de las compañías fabricantes de algunos dispositivos de electroencefalografía portable disponibles en el mercado, se exponen sus características principales, algunos trabajos encontrados que fueron realizados con los dispositivos, comparaciones entre los mismos y una discusión acerca de las ventajas y desventajas de sus características. Finalmente se concluye que a la hora de comprar un dispositivo para electroencefalografía portable es necesario tener en cuenta el uso que se le va a dar y el costo-beneficio que tiene el equipo de acuerdo con sus características. Encephalography is a technique that allows the recording of electrical activity of the brain and has been studied during the last hundred years in different areas of neuroscience. For several years, measuring equipment that are portable and that allow a good signal quality to have been researched and developed, so a literature review of the manufacturing companies of some of portable electroencephalography devices available on the market was carried out: Its main features are exposed, as well as some of the work found that were made with those, comparisons between them and a discussion about the advantages and disadvantages of their features. It is concluded that, when a portable encephalography device is bought, it’s necessary to take into consideration the use that it will be having and the cost-benefit that the device has according to its features.

Fully Printed Wearable Microfluidic Devices for High-Throughput Sweat Sampling and Multiplexed Electrochemical Analysis

Although the recent advancement in wearable biosensors provides continuous, noninvasive assessment of physiologically relevant chemical markers from human sweat, several bottlenecks still exist for its practical use. There were challenges in developing a multiplexed biosensing system with rapid microfluidic sampling and transport properties, as well as its integration with a portable potentiostat for improved interference-free data collection. Here, we introduce a clean-room free fabrication of wearable microfluidic sensors, using a screen-printed carbon master, for the electrochemical monitoring of sweat biomarkers during exercise activities. The sweat sampling is enhanced by introducing low-dimensional sensing compartments and lowering the hydrophilicity of channel layers via facile silane functionalization. The fluidic channel captures sweat at the inlet and directs the real-time sweat through the active sensing electrodes (within 40 s) for subsequent decoding and selective analyses. For proof of concept, simultaneous amperometric lactate and potentiometric ion sensing (Na⁺, K⁺, and pH) are carried out by a miniature circuit board capable of cross-talk-free signal collection and wireless signal transduction characteristics. All of the sensors demonstrated appreciable sensitivity, selectivity, stability, carryover efficiency, and repeatability. The floating potentiometric circuits eliminate the signal interference from the adjacent amperometric transducers. The fully integrated pumpless microfluidic device is mounted on the epidermis and employed for multiplexed real-time decoding of sweat during stationary biking. The regional variations in sweat composition are analyzed by human trials at the underarm and upperback locations. The presented method offers a large-scale fabrication of inexpensive high-throughput wearable sensors for personalized point-of-care and athletic applications.

Using Muse: Rapid Mobile Assessment of Brain Performance

The advent of mobile electroencephalography (mEEG) has created a means for large scale collection of neural data thus affording a deeper insight into cognitive phenomena such as cognitive fatigue. Cognitive fatigue - a neural state that is associated with an increased incidence of errorful performance - is responsible for accidents on a daily basis which at times can cost human lives. To gain better insight into the neural signature of cognitive fatigue in the present study we used mEEG to examine the relationship between perceived cognitive fatigue and human-event related brain potentials (ERPs) and electroencephalographic (EEG) oscillations in a sample of 1,000 people. As a secondary goal, we wanted to further demonstrate the capability of mEEG to accurately measure ERP and EEG data. To accomplish these goals, participants performed a standard visual oddball task on an Apple iPad while EEG data were recorded from a Muse EEG headband. Counter to traditional EEG studies, experimental setup and data collection was completed in less than seven minutes on average. An analysis of our EEG data revealed robust N200 and P300 ERP components and neural oscillations in the delta, theta, alpha, and beta bands. In line with previous findings we observed correlations between ERP components and EEG power and perceived cognitive fatigue. Further, we demonstrate here that a linear combination of ERP and EEG features is a significantly better predictor of perceived cognitive fatigue than any ERP or EEG feature on its own. In sum, our results provide validation of mEEG as a viable tool for research and provide further insight into the impact of cognitive fatigue on the human brain.

Picking Your Brains: Where and How Neuroscience Tools Can Enhance Marketing Research

The use of neuroscience tools to study consumer behavior and the decision making process in marketing has improved our understanding of cognitive, neuronal, and emotional mechanisms related to marketing-relevant behavior. However, knowledge about neuroscience tools that are used in consumer neuroscience research is scattered. In this article, we present the results of a literature review that aims to provide an overview of the available consumer neuroscience tools and classifies them according to their characteristics. We analyse a total of 219 full-texts in the area of consumer neuroscience. Our findings suggest that there are seven tools that are currently used in consumer neuroscience research. In particular, electroencephalography (EEG) and eye tracking (ET) are the most commonly used tools in the field. We also find that consumer neuroscience tools are used to study consumer preferences and behaviors in different marketing domains such as advertising, branding, online experience, pricing, product development and product experience. Finally, we identify two ready-to-use platforms, namely iMotions and GRAIL that can help in integrating the measurements of different consumer neuroscience tools simultaneously. Measuring brain activity and physiological responses on a common platform could help by (1) reducing time and costs for experiments and (2) linking cognitive and emotional aspects with neuronal processes. Overall, this article provides relevant input in setting directions for future research and for business applications in consumer neuroscience. We hope that this study will provide help to researchers and practitioners in identifying available, non-invasive and useful tools to study consumer behavior.