Article
Engineering, Biomedical
Rongrong Fu, Weishuai Li, Junxiang Chen, Mengmeng Han
Summary: This study introduces an approach for interpretable clustering in single-trial MI EEG classification, utilizing decomposed EEG data and optimized feature vectors to achieve interpretable classification results.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Engineering, Biomedical
Nitin Sadras, Omid G. Sani, Parima Ahmadipour, Maryam M. Shanechi
Summary: This study investigates the neural correlates of decision confidence using high-density EEG and shows that confidence can be reliably decoded from EEG signals before response. The findings suggest the feasibility of using non-invasive EEG-based brain-computer interfaces to improve human decision making.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Engineering, Biomedical
Rongrong Fu, Zheyu Li, Juan Wang
Summary: The study introduces an optimized GMM clustering technique that shows low sensitivity to outliers, with experimental verification demonstrating high accuracy levels. The results exceed traditional methods and show comparable improvements when combined with state-of-the-art clustering techniques.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Neurosciences
Syanah C. Wynn, Erika Nyhus, Ole Jensen
Summary: This study found that both older and younger adults were able to encode targets paired with distractors, and the level of alpha power modulation during encoding predicted recognition success. Older adults showed signs of higher distractibility, but this did not harm their episodic memory for target information. The research also demonstrated that older adults only modulated alpha power during high distraction, indicating that both age groups can successfully employ inhibitory control mechanisms but older adults fail to do so when distraction is minimal.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2022)
Article
Food Science & Technology
Saifon Phothisuwan, Phanit Koomhin, Nirundorn Matan, Narumol Matan
Summary: The study demonstrated that using carnauba wax containing 0.08% orange oil could maintain desired qualities of the fruit and provide moderate sensory acceptance. Additionally, EEG results showed that consumption of orange oil-treated fruit could enhance alertness in human brain function.
LWT-FOOD SCIENCE AND TECHNOLOGY
(2021)
Article
Neurosciences
Cynthia R. Hunter
Summary: This study investigated neural markers for listening effort and listening-related fatigue. The changes in alpha and theta oscillatory power were found to be associated with listening effort and fatigue. Furthermore, hearing loss and self-reported fatigue influenced tonic changes in oscillatory power.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Neurosciences
Ioannis Delis, Robin A. A. Ince, Paul Sajda, Qi Wang
Summary: This study investigated how the human brain processes multisensory information during perceptual judgments, revealing a multisensory enhancement of neural representations of active sensing leading to faster and more accurate decisions. Furthermore, interactions between different sensory representations were identified, contributing to the prediction of multisensory decision-making performance.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Automation & Control Systems
Feifei Qi, Wei Wu, Zhu Liang Yu, Zhenghui Gu, Zhenfu Wen, Tianyou Yu, Yuanqing Li
Summary: The proposed method, spatiotemporal-filtering-based channel selection (STECS), automatically identifies a designated number of discriminative channels in EEG data by leveraging spatiotemporal information. Evaluations on three motor imagery EEG datasets show that STECS achieves comparable classification performance with only half of the channels used by state-of-the-art spatiotemporal filtering algorithms, and significantly outperforms existing channel selection methods, indicating its potential for simplifying BCI setups and improving practical utility.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Neurosciences
Rongrong Fu, Dong Xu, Weishuai Li, Peiming Shi
Summary: This study proposes a spatial domain filtering based EEG feature extraction method, which extracts multi-dimensional EEG features and establishes an optimal feature criterion and projection space to obtain optimized EEG features. Experimental results show high accuracy in identifying two-dimensional and three-dimensional optimal EEG features, providing an alternative solution for BCI application.
COGNITIVE NEURODYNAMICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Zhihua Huang, Kun Jiang, Jing Li, Wenxing Zhu, Huiru Zheng, Yiwen Wang
Summary: This study explores the discriminability of single-trial EEG corresponding to different decisions using a machine learning approach. Results show the discriminability between cooperation and aggression decisions, mainly from EEG information below 40 Hz. Contributions of different brain regions to the discriminability are consistent with existing knowledge on the cognitive mechanism of decision-making, confirming the reliability of the conclusions.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2022)
Article
Chemistry, Analytical
Emad Alyan, Naufal M. Saad, Nidal Kamel, Mohd Zuki Yusoff, Mohd Azman Zakariya, Mohammad Abdul Rahman, Christophe Guillet, Frederic Merienne
Summary: This study investigates the effects of workplace noise on neural activity and alpha asymmetries of the prefrontal cortex during mental stress conditions. The findings suggest that workplace noise can increase cortical activity and induce stress reactions, with a greater significant right frontal activation observed in the noisy workplace group. This study provides critical information on the impact of workplace noise-related stress that may be overlooked during mental stress evaluations.
Article
Psychology, Multidisciplinary
Zetong He, Lidan Cui, Shunmin Zhang, Guibing He
Summary: This study investigates the prediction of participants' single-trial choice in a rock-paper-scissors game using EEG signals. The results demonstrate that CSP features have a strong classification ability in multichoice decision-making prediction.
Article
Neurosciences
Grace M. Clements, Mate Gyurkovics, Kathy A. Low, Diane M. Beck, Monica Fabiani, Gabriele Gratton
Summary: The research investigated the role of alpha and theta power in multimodal competition, finding that alpha waves help maintain representations and protect them from interference, while theta waves may facilitate updating when needed. Results showed that responses to visual and auditory stimuli differed with alpha waves depending on eye status, while theta power did not interact with eye status.
Article
Computer Science, Artificial Intelligence
Xiuxin Xia, Yan Shi, Pengwei Li, Xiaosong Liu, Jingjing Liu, Hong Men
Summary: Currently, the evaluation of food sensory largely relies on artificial sensory evaluation and machine perception. However, the former is influenced by subjective factors and the latter fails to capture human feelings. This article proposes a Frequency Band Attention Network (FBANet) for distinguishing differences in food odor using olfactory electroencephalogram (EEG). The FBANet effectively mines the olfactory EEG data information and accurately distinguishes between eight food odors, presenting a new approach for food sensory evaluation.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Yasue Mitsukura, Yuuki Tazawa, Risa Nakamura, Brian Sumali, Tsubasa Nakagawa, Satoko Hori, Masaru Mimura, Taishiro Kishimoto
Summary: This study recorded EEG data from 40 depression patients during conversation and compared them with 40 healthy subjects. The results showed significant spectral differences between depression patients and healthy individuals, as well as between patients of different severity levels and healthy individuals. Significant differences were also observed at multiple frequencies when comparing patients taking different medications. However, the spectral differences remained significant between non-medicated patients and healthy individuals.
Article
Neurosciences
Bin Lou, Wha-Yin Hsu, Paul Sajda
JOURNAL OF NEUROSCIENCE
(2015)
Article
Multidisciplinary Sciences
Francisco Pereira, Bin Lou, Brianna Pritchett, Samuel Ritter, Samuel J. Gershman, Nancy Kanwisher, Matthew Botvinick, Evelina Fedorenko
NATURE COMMUNICATIONS
(2018)
Article
Radiology, Nuclear Medicine & Medical Imaging
Seo Yeon Youn, Moon Hyung Choi, Young Joon Lee, Robert Grimm, Heinrich von Busch, Dongyeob Han, Yohan Son, Bin Lou, Ali Kamen
Summary: The study evaluated the accuracy of prostate volume estimates calculated from the ellipsoid formula using the anteroposterior (AP) diameter measured on ultrasound (US) and magnetic resonance imaging (MRI). The results showed that the volume was underestimated on US and overestimated on MRI.
Article
Medicine, General & Internal
David J. Winkel, Christian Wetterauer, Marc Oliver Matthias, Bin Lou, Bibo Shi, Ali Kamen, Dorin Comaniciu, Hans-Helge Seifert, Cyrill A. Rentsch, Daniel T. Boll
Article
Medical Informatics
Bin Lou, Semihcan Doken, Tingliang Zhuang, Danielle Wingerter, Mishka Gidwani, Nilesh Mistry, Lance Ladic, Ali Kamen, Mohamed E. Abazeed
LANCET DIGITAL HEALTH
(2019)
Article
Neurosciences
Jose Sanchez-Bornot, Roberto C. Sotero, J. A. Scott Kelso, Ozguer Simsek, Damien Coyle
Summary: This study proposes a multi-penalized state-space model for analyzing unobserved dynamics, using a data-driven regularization method. Novel algorithms are developed to solve the model, and a cross-validation method is introduced to evaluate regularization parameters. The effectiveness of this method is validated through simulations and real data analysis, enabling a more accurate exploration of cognitive brain functions.
