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• People with autism are less efficient in filtering distractors and staying in-task when compared to their healthy counterparts. • Some people with autism show abnormal brain signalling reflected by heightened theta-band functional excitation/inhibition (fE/I) ratio. • Heightened theta-band fE/I is associated with more efficient interference control. How abnormal brain signaling impacts cognition in autism spectrum disorder (ASD) remained elusive. This study aimed to investigate the local and global brain signaling in ASD indicated by theta-band functional excitation-inhibition (fE/I) ratio and explored psychophysiological relationships between fE/I, cognitive deficits, and ASD symptomatology. A total of 83 ASD and typically developing (TD) individuals participated in this study. Participants' interference control and set-shifting abilities were assessed. Resting-state electroencephalography (EEG) was used for estimating theta-band fE/I ratio. ASD individuals (n = 31 without visual EEG abnormality; n = 22 with visual EEG abnormality) generally performed slower in a cognitive task tapping interference control and set-maintenance abilities, but only ASD individuals with visually abnormal EEG performed significantly slower than their TD counterparts (Bonferroni-corrected ps <.001). Heightened theta-band fE/I ratios at the whole-head level, left and right hemispheres were observed in the ASD subgroup without visual EEG abnormality only (Bonferroni-corrected ps <.001), which remained highly significant when only data from medication-naïve participants were analyzed. In addition, higher left hemispheric fE/I ratios in ASD individuals without visual EEG abnormality were significantly correlated with faster interference control task performance, in turn faster reaction time was significantly associated with less severe restricted, repetitive behavior (Bonferroni-corrected ps ≤.0017). Differential theta-band fE/I within the ASD population. Heightened theta-band fE/I in ASD without visual EEG abnormality may be associated with more efficient filtering of distractors and a less severe ASD symptom manifestation. Brain signaling, indicated by theta-band fE/I, was different in ASD subgroups. Only ASD with visually-normal EEG showed heightened theta-band fE/I, which was associated with faster processing of visual distractors during a cognitive task. More efficient distractor filtering was associated with less restricted, repetitive behaviors. [ABSTRACT FROM AUTHOR]

Embodied cognition explores the intricate interaction between the brain, body, and the surrounding environment. The advancement of mobile devices, such as immersive interactive computing and wireless electroencephalogram (EEG) devices, has presented new challenges and opportunities for studying embodied cognition. To address how mobile technology within immersive hybrid settings affects embodied cognition, we propose a target detection multitask incorporating mixed body movement interference and an environmental distraction light signal. We aim to investigate human embodied cognition in immersive projector-based augmented reality (IPAR) scenarios using wireless EEG technology. We recruited and engaged fifteen participants in four multitasking conditions: standing without distraction (SND), walking without distraction (WND), standing with distraction (SD), and walking with distraction (WD). We pre-processed the EEG data using Independent Component Analysis (ICA) to isolate brain sources and K-means clustering to categorize Independent Components (ICs). Following that, we conducted time-frequency and correlation analyses to identify neural dynamics changes associated with multitasking. Our findings reveal a decline in behavioral performance during multitasking activities. We also observed decreases in alpha and beta power in the frontal and motor cortex during standing target search tasks, decreases in theta power, and increases in alpha power in the occipital lobe during multitasking. We also noted perturbations in theta band power during distraction tasks. Notably, physical movement induced more significant fluctuations in the frontal and motor cortex than distractions from social environment light signals. Particularly in scenarios involving walking and multitasking, there was a noticeable reduction in beta suppression. Our study underscores the importance of brain-body collaboration in multitasking scenarios, where the simultaneous engagement of the body and brain in complex tasks highlights the dynamic nature of cognitive processes within the framework of embodied cognition. Furthermore, integrating immersive augmented reality technology into embodied cognition research enhances our understanding of the interplay between the body, environment, and cognitive functions, with profound implications for advancing human-computer interaction and elucidating cognitive dynamics in multitasking.

Embodied cognition explores the intricate interaction between the brain, body, and the surrounding environment. The advancement of mobile devices, such as immersive interactive computing and wireless electroencephalogram (EEG) devices, has presented new challenges and opportunities for studying embodied cognition. To address how mobile technology within immersive hybrid settings affects embodied cognition, we propose a target detection multitask incorporating mixed body movement interference and an environmental distraction light signal. We aim to investigate human embodied cognition in immersive projector-based augmented reality (IPAR) scenarios using wireless EEG technology. We recruited and engaged fifteen participants in four multitasking conditions: standing without distraction (SND), walking without distraction (WND), standing with distraction (SD), and walking with distraction (WD). We pre-processed the EEG data using Independent Component Analysis (ICA) to isolate brain sources and K-means clustering to categorize Independent Components (ICs). Following that, we conducted time-frequency and correlation analyses to identify neural dynamics changes associated with multitasking. Our findings reveal a decline in behavioral performance during multitasking activities. We also observed decreases in alpha and beta power in the frontal and motor cortex during standing target search tasks, decreases in theta power, and increases in alpha power in the occipital lobe during multitasking. We also noted perturbations in theta band power during distraction tasks. Notably, physical movement induced more significant fluctuations in the frontal and motor cortex than distractions from social environment light signals. Particularly in scenarios involving walking and multitasking, there was a noticeable reduction in beta suppression. Our study underscores the importance of brain-body collaboration in multitasking scenarios, where the simultaneous engagement of the body and brain in complex tasks highlights the dynamic nature of cognitive processes within the framework of embodied cognition. Furthermore, integrating immersive augmented reality technology into embodied cognition research enhances our understanding of the interplay between the body, environment, and cognitive functions, with profound implications for advancing human-computer interaction and elucidating cognitive dynamics in multitasking. [ABSTRACT FROM AUTHOR]

Over the last two decades, there has been a tremendous increase in research activity on brain connectivity studies and its application in different neurological disorders. Studies have been focused on different connectivity patterns generated and potential biomarkers that could be derived to find the etymology of the disorder. In this review, the focus is on the utilization of wireless electroencephalogram monitoring system for functional connectivity analysis and its capacity for deciphering neurological disorders. The paper reviews different methods adopted to estimate connectivity and the possible convergence of connectivity patterns in four neurological disorders: epilepsy, autism spectrum disorder, Alzheimer and Parkinson's disease. The paper reviews the current status of connectivity research in the aforementioned neurological disorders and its potential in developing a smart e‐health service. [ABSTRACT FROM AUTHOR]

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.

This study compared the signal quality of six commercially available electroencephalography (EEG) signal acquisition systems in order to evaluate their application in a brain-computer interface (BCI). This is one of the largest studies in terms of subjects and systems focusing on comparing different EEG systems, involving the whole variety in terms of amplifier (research grade, consumer grade), electrode type (gel-based, saline-based, dry, active, passive), transmission technique (wired, wireless), and cost. We established an approach to evaluate the signal quality by means of a steady-state visually evoked potentials (SSVEP) experiment. This demonstrated that although high-end traditional EEG equipment may be the best choice for clinical applications, low-end wireless research grade gel-based EEG systems are comparable in terms of signal quality and therefore may be an effective alternative to BCIs developed for real environments. Other factors, such as end user and application, should also be considered when deciding which EEG system is best suited for a BCI. [ABSTRACT FROM AUTHOR]

This work presents a wireless multichannel electroencephalogram (EEG) recording system featuring lossless and near-lossless compression of the digitized EEG signal. Two novel, low-complexity, efficient compression algorithms were developed and tested in a low-power platform. The algorithms were tested on six public EEG databases comparing favorably with the best compression rates reported up to date in the literature. In its lossless mode, the platform is capable of encoding and transmitting 59-channel EEG signals, sampled at 500 Hz and 16 bits per sample, at a current consumption of 337 $\mu$A per channel; this comes with a guarantee that the decompressed signal is identical to the sampled one. The near-lossless mode allows for significant energy savings and/or higher throughputs in exchange for a small guaranteed maximum per-sample distortion in the recovered signal. Finally, we address the tradeoff between computation cost and transmission savings by evaluating three alternatives: sending raw data, or encoding with one of two compression algorithms that differ in complexity and compression performance. We observe that the higher the throughput (number of channels and sampling rate) the larger the benefits obtained from compression. [ABSTRACT FROM PUBLISHER]

This study compared the performance of a low-cost wireless EEG system to a research-grade EEG system on an auditory oddball task designed to elicit N200 and P300 ERP components. Participants were 15 healthy adults (6 female) aged between 19 and 40 ( M = 28.56; SD = 6.38). An auditory oddball task was presented comprising 1,200 presentations of a standard tone interspersed by 300 trials comprising a deviant tone. EEG was simultaneously recorded from a modified Emotiv EPOC and a NeuroScan SynAmps RT EEG system. The modifications made to the Emotiv system included attaching research grade electrodes to the Bluetooth transmitter. Additional modifications enabled the Emotiv system to connect to a portable impedance meter. The cost of these modifications and portable impedance meter approached the purchase value of the Emotiv system. Preliminary analyses revealed significantly more trials were rejected from data acquired by the modified Emotiv compared to the SynAmps system. However, the ERP waveforms captured by the Emotiv system were found to be highly similar to the corresponding waveform from the SynAmps system. The latency and peak amplitude of N200 and P300 components were also found to be similar between systems. Overall, the results indicate that, in the context of an oddball task, the ERP acquired by a low-cost wireless EEG system can be of comparable quality to research-grade EEG acquisition equipment. [ABSTRACT FROM AUTHOR]

The majority of neuroergonomics studies are focused mainly on investigating the interaction between operators and automated systems. Far less attention has been dedicated to the investigation of brain processes in more traditional workplaces, such as manual assembly, which are still ubiquitous in industry. The present study investigates whether assembly workers’ attention can be enhanced if they are instructed with which hand to initiate the assembly operation, as opposed to the case when they can commence the operation with whichever hand they prefer. For this aim, we replicated a specific workplace, where seventeen participants in the study simulated a manual assembly operation of the rubber hoses that are used in vehicle hydraulic brake systems, while wearing wireless electroencephalography (EEG). The specific EEG feature of interest for this study was the P300 components’ amplitude of the event-related potential (ERP), as it has previously been shown that it is positively related to human attention. The behavioral attention-related modality of reaction times (RTs) was also recorded. Participants were presented with two distinct tasks during the simulated operation, which were counterbalanced across participants. In the first task, digits were used as indicators for the operation initiation (Numbers task), where participants could freely choose with which hand they would commence the action upon seeing the digit. In the second task, participants were presented with arrows, which served as instructed operation initiators (Arrows task), and they were instructed to start each operation with the hand that corresponded to the arrow direction. The results of this study showed that the P300 amplitude was significantly higher in the instructed condition. Interestingly, the RTs did not differ across any task conditions. This, together with the other findings of this study, suggests that attention levels can be increased using instructed responses without compromising work performance or operators’ well-being, paving the way for future applications in manual assembly task design.

Continuous and objective measurement of the user attention state still represents a major challenge in the ergonomics research. Recently available wearable electroencephalography (EEG) opens new opportunities for objective and continuous evaluation of operators’ attention, which may provide a new paradigm in ergonomics. In this study, wearable EEG was recorded during simulated assembly operation, with the aim to analyse P300 event-related potential component, which provides reliable information on attention processing. In parallel, reaction times (RTs) were recorded and the correlation between these two attention-related modalities was investigated. Negative correlation between P300 amplitudes and RTs has been observed on the group level (p < .001). However, on the individual level, the obtained correlations were not consistent. As a result, we propose the P300 amplitude for accurate attention monitoring in ergonomics research. On the other hand, no significant correlation between RTs and P300 latency was found on group, neither on individual level. Practitioner Summary:Ergonomic studies of assembly operations mainly investigated physical aspects, while mental states of the assemblers were not sufficiently addressed. Presented study aims at attention tracking, using realistic workplace replica. It is shown that drops in attention could be successfully traced only by direct brainwave observation, using wireless electroencephalographic measurements. [ABSTRACT FROM PUBLISHER]

• The new EEG device "Mentalab Explore" is valid and reliable system to evaluate resting state EEG spectral features. • There were no significant differences between clinical and consumer-grade EEG devices on alpha peak frequencies or suppression. • The PSD, alpha peak frequency, and suppression levels of Mentalab Explore EEG device were consistent between the two measurements carried out 24-h apart. Technological advancements in neuroscience have provided many conveniences to scientists, researchers, and consumers. The emerging electroencephalography (EEG) devices are good examples for it. The objective of this study was to investigate the validity and reliability of a new wireless EEG device Mentalab Explore for resting-state EEG (rsEEG) recordings in eyes open and eyes closed conditions. Twenty-three healthy subjects were recruited for the study. The subjects visited the laboratory on two occasions. On the first day, both devices were used to record rsEEG data, and after 24 h, only the Mentalab Explore was used to record rsEEG for test–retest reliability analysis. We compared the alpha peak frequency, suppression, and mean power between the two devices. Intraclass correlation coefficient was calculated for test–retest reliability analysis. Power spectral density (PSD) was calculated using Welch method. The PSD (eyes closed p < 0.0001; eyes open p = 0.01–0.0001), alpha peak frequency (p < 0.0001), and alpha suppression (p = 0.002–0.0001) from the two EEG devices as well as the test–retest results from the Mentalab device were significantly correlated. There were no significant differences in alpha peak frequency or suppression between the clinical-grade and the new devices for O1 and O2 channels in eyes-closed condition. The two measurements completed ∼24 h apart using the Mentalab system were similar for all the variables. We showed that the consumer-grade Mentalab Explore with gel electrodes is a reliable and valid EEG recording device for rsEEG spectral features. [ABSTRACT FROM AUTHOR]

Acquisition of event-related potentials (ERPs) requires a nearly perfect synchronization between the stimulus player and the EEG acquisition unit that clinical systems implement at hardware level by means of a wired link. Out of clinical context, current brain-computer interface technology offers wireless and wearable EEG headsets that provide ubiquitous EEG acquisition. However, they are not adequate for ERPs acquisition since they lack the physical wire with the stimulus player. In this paper, we propose a novel technique devoted to provide a solution to this problem by means of a bio-synchronization approach. This technique adds to the stimulus data, a tagged audio preamble for synchronization (TAP-S) that embeds a synchronization mechanism in its physiological response based on pseudo random sequences. In this way, the EEG data elicited by the preamble and the stimulus are recorded together and the stimulus onset can be directly extracted from the EEG data by preamble detection. TAP-S is tailored to work with any low-cost multimedia player and wireless EEG headsets. Our preliminary results reveal TAP-S as a first, promising, and low-cost approach that, after further improvement, could enable remote processing of ERPs with wireless acquisition with application in telemedicine, ambient assisted living, or brain-computer interfaces. [ABSTRACT FROM AUTHOR]

Background: Electroencephalography (EEG) is a widely used neuroimaging technique with applications in healthcare, research, assessment, treatment, and neurorehabilitation. Conventional EEG systems require extensive setup time, expensive equipment, and expertise to utilize and therefore are often limited to clinical or laboratory settings. Technological advancements have made it possible to develop wireless EEG systems with dry electrodes to reduce many of these barriers. However, due to the lack of homogeneity in hardware, electrode evaluation, and methodological procedures the clinical acceptance of these systems has been limited.Methods: In this investigation the validity of a wireless dry electrode system compared to a conventional wet electrode system was assessed, while addressing methodological limitations. In Experiment 1, the signal output of both EEG systems was examined at Fz, C3, Cz, C4, and Pz using a conductive head model and generated test signals at 2.5 Hz, 10 Hz, and 39 Hz. In Experiment 2, two-minutes of eyes-closed and eyes-open EEG data was recorded simultaneously with both devices from the adjacent electrode sites in a sample of healthy adults.Results: Between group effects and frequency*device and electrode*device interactions were assessed using a mixed ANOVA for the simulated and in vivo signal output, producing no significant effects . Bivariate correlation coefficients were calculated to assess the relationship between electrode pairs during the simultaneous in vivo recordings, indicating a significant positive relationship (all p's < .05) and larger correlation coefficients (r > ± 0.5) between the dry and wet electrode signal amplitude were observed for theta, alpha, beta 1, beta 2, beta 3, and gamma in both the eyes-closed and eyes-open conditions.Conclusions: This report demonstrates preliminary but compelling evidence that EEG data recorded from the wireless dry electrode system is comparable to data recorded from a conventional system. Small correlation values in delta activity were discussed in relation to minor differences in hardware filter settings, variation in electrode placement, and participant artifacts observer during the simultaneous EEG recordings. Study limitations and impact of this research on neurorehabilitation were discussed. [ABSTRACT FROM AUTHOR]

Abstract: Studying the brain in its natural state remains a major challenge for neuroscience. Solving this challenge would not only enable the refinement of cognitive theory, but also provide a better understanding of cognitive function in the type of complex and unpredictable situations that constitute daily life, and which are often disturbed in clinical populations. With mobile EEG, researchers now have access to a tool that can help address these issues. In this paper we present an overview of technical advancements in mobile EEG systems and associated analysis tools, and explore the benefits of this new technology. Using the example of motor imagery (MI) we will examine the translational potential of MI-based neurofeedback training for neurological rehabilitation and applied research. [Copyright &y& Elsevier]

To build a low-cost, small, and wireless electroencephalogram ( EEG) system suitable for field recordings, we merged consumer EEG hardware with an EEG electrode cap. Auditory oddball data were obtained while participants walked outdoors on university campus. Single-trial P300 classification with linear discriminant analysis revealed high classification accuracies for both indoor (77%) and outdoor (69%) recording conditions. We conclude that good quality, single-trial EEG data suitable for mobile brain-computer interfaces can be obtained with affordable hardware. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a complete non-invasive Wireless acquisition system based on dry electrodes for electroencephalograms (WiDE-EEG) with emphasis in the electronic system design. The WiDE-EEG is composed by a 2.4GHz radio-frequency (RF) transceiver, biopotential acquisition electronics and dry electrodes. The WiDE-EEG can acquire electroencephalogram (EEG) signals from 5 unipolar channels, with a resolution of 16bits and minimum analog amplitude of 9.98μVpp, at a sampling rate of 1000samples/s/channel and sends them to a processing unit through RF in a 10m range. The analog channels were optimized for EEG signals (with amplitudes in the range 70–100μV) and present the following characteristics: a signal gain of 66dB and a common mode rejection ratio of 56.5dB. Each electrode is composed by 16 microtip structures that were fabricated through bulk micromachining of a 〈100〉-type silicon substrate in a potassium hydroxide (KOH) solution. The microtips present solid angles of 54.7°, a height of 100–200μm and 2μm spaced apart. The electrodes have a thin layer (obtained by sputtering) of iridium oxide (IrO) to guaranty their biocompatibility and improve the contact with the skin. These dry electrodes are in direct contact with the electrolyte fluids of the inner skin layers, and avoid the use of conductive gels. The complete WiDE-EEG occupies a volume of 9cm×8.5cm×1cm, which makes it suitable for true mobility of the subjects and at the same time allows high data transfer rates. Since the WiDE-EEG is battery-powered, it overcomes the need of galvanic isolation for ensuring patient safety observed on conventional EEG instrumentation systems. The WiDE-EEG presents a total power consumption of 107mW, divided as follows: the acquisition system contributes with 10mW per channel, whereas the commercial MICAz module contributes with 57mW (e.g., 24mW from the microcontroller and 33mW from the RF chip). The WiDE-EEG also presents autonomy of about 25h with two class AA 1.5V batteries. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]