@article{seo2021derivation,

title = {Derivation of EEG Spectrum-based Feature Parameters for Mental Fatigue Determination},

author = {Ssang-Hee Seo},

doi = {https://doi.org/10.22156/CS4SMB.2021.11.10.010},

year  = {2021},

date = {2021-10-28},

journal = {Journal of Convergence for Information Technology},

volume = {11},

number = {10},

pages = {10--19},

publisher = {Convergence Society for SMB},

abstract = {In this paper, we tried to derive characteristic parameters that reflect mental fatigue through EEG measurement and analysis. For this purpose, mental fatigue was induced through a resting state with eyes closed and performing subtraction operations in mental arithmetic for 30 minutes. Five subjects participated in the experiment, and all subjects were right-handed male students in university, with an average age of 25.5 years. Spectral analysis was performed on the EEG collected at the beginning and the end of the experiment to derive feature parameters reflecting mental fatigue. As a result of the analysis, the absolute power of the alpha band in the occipital lobe and the temporal lobe increased as the mental fatigue increased, while the relative power decreased. Also, the difference in power between resting state and task state showed that the relative power was larger than the absolute power. These results indicate that alpha relative power in the occipital lobe and temporal lobe is a feature parameter reflecting mental fatigue. The results of this study can be utilized as feature parameters for the development of an automated system for mental fatigue determination such as fatigue and drowsiness while driving.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{lim2021superior,

title = {Superior Facilitation of an Action Observation Network by Congruent Character Movements in Brain--Computer Interface Action-Observation Games},

author = {Hyunmi Lim and Jeonghun Ku},

doi = {https://doi.org/10.1089/cyber.2020.0231},

year  = {2021},

date = {2021-08-04},

journal = {Cyberpsychology, Behavior, and Social Networking},

volume = {24},

number = {8},

pages = {566--572},

publisher = {Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New~…},

abstract = {Action observation (AO) is a promising strategy for promoting motor function in neural rehabilitation. Recently, brain–computer interface (BCI)-AO game rehabilitation, which combines AO therapy with BCI technology, has been introduced to improve the effectiveness of rehabilitation. This approach can improve motor learning by providing feedback, which can be interactive in an observation task, and the game contents of the BCI-AO game paradigm can affect rehabilitation. In this study, the effects of congruent rather than incongruent feedback in a BCI-AO game on mirror neurons were investigated. Specifically, the mu suppression with congruent and incongruent BCI-AO games was measured in 17 healthy adults. The mu suppression in the central motor cortex was significantly higher with the congruent BCI-AO game than with the incongruent one. In addition, the satisfaction evaluation results were excellent for the congruent case. These results support the fact that providing feedback congruent with the motion of an action video facilitates mirror neuron activity and can offer useful guidelines for the design of BCI-AO games for rehabilitation},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{lin2021age,

title = {Age-related differences in alpha and beta band activity in sensory association brain areas during challenging sensory tasks},

author = {Chun-Ling Lin and Ya-Wen Hsieh and Hui-Ya Chen},

doi = {https://doi.org/10.1016/j.bbr.2021.113279},

year  = {2021},

date = {2021-06-25},

journal = {Behavioural Brain Research},

volume = {408},

pages = {113279},

publisher = {Elsevier},

abstract = {Sensory challenges to postural balance are daily threats for elderly individuals. This study examined electroencephalography (EEG) in alpha and beta bands in sensory association areas during the Sensory Organization Test, involving withdrawal of visual or presenting misleading somatosensory inputs, in twelve young and twelve elderly participants. The results showed stepwise deterioration in behavioral performance in four conditions, with group effects that were amplified with combined sensory challenges. With eye closure, alpha and beta activities increased in all sensory association areas. Fast beta activity increased in the bilateral parietal-temporal-occipital areas. Misleading somatosensory information effects on EEG activity were of smaller amplitude than eye closure effects and in a different direction. Decreased alpha activity in left parietal-temporal-occipital areas and decreased beta and fast beta activities in bilateral parietal-temporal-occipital areas were significant. Elderly participants had increased fast beta activity in the left temporal-occipital and bilateral occipital areas, indicative of sustained efforts that they made in all sensory conditions. Similar to the young participants, elderly participants with eyes closed showed increased alpha activity, although to a smaller degree, in bilateral temporal-occipital and left occipital areas. This might indicate a lack of efficacy in redistributing relative sensory weights when elderly participants dealt with eye closure. In summary, EEG power changes did not match the stepwise deterioration in behavioral data, but reflected different sensory strategies adopted by young and elderly participants to cope with eye closure or misleading somatosensory information based on the efficacy of these different strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rustamov2021spatial,

title = {Spatial and frequency-specific electrophysiological signatures of tonic pain recovery in humans},

author = {Nabi Rustamov and Lokesh Sharma and Sarah N Chiang and Carrie Burk and Simon Haroutounian and Eric C Leuthardt},

doi = {https://doi.org/10.1016/j.neuroscience.2021.04.008},

year  = {2021},

date = {2021-04-21},

urldate = {2021-01-01},

journal = {Neuroscience},

volume = {465},

pages = {23–37},

publisher = {Elsevier},

abstract = {The objective of this study was to comprehensively investigate patterns of brain activities associated with pain recovery following experimental tonic pain in humans. Specific electrophysiological features of pain recovery may either be monitored or be modulated through neurofeedback (NF) as a novel chronic pain treatment. The cold pressor test was applied with simultaneous electroencephalogram (EEG) recording. EEG data were acquired, and analyzed to define: (1) EEG power topography patterns of pain recovery; (2) source generators of pain recovery at cortical level; (3) changes in functional connectivity associated with pain recovery; (4) features of phase-amplitude coupling (PAC) as it relates to pain recovery. The novel finding of this study is that recovery from pain was characterized by significant theta power rebound at the left fronto-central area. The sources of theta power over-recovery were located in the left dorsolateral prefrontal cortex (DLPFC), cingulate cortex, left insula and contralateral sensorimotor cortex. These effects were paralleled by theta band connectivity increase within hemispheres in a prefrontal–somatosensory network and interhemispherically between prefrontal and parietal areas. In addition, this study revealed significant reduction in PAC between theta/alpha and gamma oscillations during recovery period following tonic pain. These findings have largely been replicated across two identical sessions. Our study emphasizes the association between pain recovery and left lateral prefrontal theta power rebound, and significant over-recovery of functional connectivity in prefrontal-sensorimotor neural network synchronized at theta frequencies. These findings may provide basis for chronic pain treatment by modulating neural oscillations at theta frequencies in left prefrontal cortex.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kim2021effects,

title = {Effects of Changes to Architectural Elements on Human Relaxation-Arousal Responses: Based on VR and EEG},

author = {Sanghee Kim and Hyejin Park and Seungyeon Choo},

doi = {https://doi.org/10.3390/ijerph18084305},

year  = {2021},

date = {2021-04-19},

journal = {International Journal of Environmental Research and Public Health},

volume = {18},

number = {8},

pages = {4305},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {This study combines electroencephalogram (EEG) with virtual reality (VR) technologies to measure the EEG responses of users experiencing changes to architectural elements. We analyze the ratio of alpha to beta waves (RAB) indicators to determine the pre- and poststimulation changes. In our methodology, thirty-three females experience using private rooms in a postpartum care center participated in the experiment. Their brain waves are measured while they are experiencing the VR space of a private room in a postpartum care center. Three architectural elements (i.e., aspect ratio of space, ceiling height, and window ratio) are varied in the VR space. In addition, a self-report questionnaire is administered to examine whether the responses are consistent with the results of the EEG response analysis. As a result, statistically significant differences (p < 0.05) are observed in the changes in the RAB indicator values of the pre- and poststimulation EEG while the subjects are experiencing the VR space where the architectural elements are varied. That is, the effects of the changes to architectural elements on users’ relaxation-arousal responses are statistically verified. Notably, in all the RAB indicator values where significant differences are observed, the poststimulation RAB decreases in comparison to the prestimulus ratios, which is indicative of the arousal response. However, the arousal levels vary across the architectural elements, which implies it would be possible to find out the elements that could induce less arousal response using the proposed method. Moreover, following the experience in the VR space, certain lobes of the brain (F4 and P3 EEG channels) show statistically significant differences in the relaxation-arousal responses. Unlike previous studies, which measured users’ physiological responses to abstract and primordial spatial elements, this study extends the boundaries of the literature by applying the architectural elements applicable to design in practice},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{eldeeb2021trial,

title = {Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD},

author = {Safaa Eldeeb and Busra T Susam and Murat Akcakaya and Caitlin M Conner and Susan W White and Carla A Mazefsky},

url = {https://www.nature.com/articles/s41598-021-85362-8},

year  = {2021},

date = {2021-03-16},

journal = {Scientific Reports},

volume = {11},

number = {1},

pages = {1--13},

publisher = {Nature Publishing Group},

abstract = {Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is often accompanied by impaired emotion regulation (ER). There has been increasing emphasis on developing evidence-based approaches to improve ER in ASD. Electroencephalography (EEG) has shown success in reducing ASD symptoms when used in neurofeedback-based interventions. Also, certain EEG components are associated with ER. Our overarching goal is to develop a technology that will use EEG to monitor real-time changes in ER and perform intervention based on these changes. As a first step, an EEG-based brain computer interface that is based on an Affective Posner task was developed to identify patterns associated with ER on a single trial basis, and EEG data collected from 21 individuals with ASD. Accordingly, our aim in this study is to investigate EEG features that could differentiate between distress and non-distress conditions. Specifically, we investigate if the EEG time-locked to the visual feedback presentation could be used to classify between WIN (non-distress) and LOSE (distress) conditions in a game with deception. Results showed that the extracted EEG features could differentiate between WIN and LOSE conditions (average accuracy of 81%), LOSE and rest-EEG conditions (average accuracy 94.8%), and WIN and rest-EEG conditions (average accuracy 94.9%).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}