Article
Multidisciplinary Sciences
Paola S. Oviedo, Luis M. Baraldo, Alejandro Cadranel
Summary: This work investigates the concept of engineering differential wave function overlap between excited states within a molecular chromophore to control excited state wave function symmetries, which leads to differential orbital overlap and low-energy trajectories within the excited state surface. By exploring two donor-acceptor assemblies, it was found that visible light absorption can prepare excited states with different wave function symmetry, allowing for energy transfer and backelectron transfer. The presence of kinetic barriers prevents excited state equilibration, providing a strategy to avoid energy dissipation in energy conversion or photoredox catalytic schemes.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Computer Science, Information Systems
Sihong Wei, Junfeng Gao, Yong Yang, Neal Xiong, Jiaqi Zhang, Jian Song, Qianruo Kang, Yaqian Li, Haoan Lv
Summary: Although it is known that multiple brain networks are involved in deception, the directionality of these networks is still unclear. This study investigated the effective connectivity of brain networks during deception and found that lying neural oscillations have specific patterns of information interaction. The results showed that all frequency bands can accurately detect deception and innocence. Furthermore, deception was associated with stronger information flow in frontoparietal, frontotemporal, and temporoparietal networks, as well as activation of the prefrontal cortex across all frequency ranges.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Chemistry, Analytical
Mahrad Ghodousi, Jachin Edward Pousson, Aleksandras Voicikas, Valdis Bernhofs, Evaldas Pipinis, Povilas Tarailis, Lana Burmistrova, Yuan-Pin Lin, Inga Griskova-Bulanova
Summary: This study investigates the neural correlates of intentional emotion transfer by the music performer through EEG connectivity patterns. The findings suggest that EEG-based connectivity in beta and gamma frequency ranges can effectively reflect the state of the networks involved in the emotional transfer, while the utility of low frequency bands (delta, theta, alpha) remains questionable.
Article
Neurosciences
Daniel S. Weisholtz, Gabriel Kreiman, David A. Silbersweig, Emily Stern, Brannon Cha, Tracy Butler
Summary: This study found that emotional valence can be decoded from intracranial electroencephalography signals in the left medial orbitofrontal cortex and middle temporal gyrus, suggesting the presence of task-independent emotional valence information in these regions.
SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE
(2022)
Article
Neurosciences
Alessio Perinelli, Sara Assecondi, Chiara F. Tagliabue, Veronica Mazza
Summary: This study found that there is a shift from posterior to anterior areas in the neural activity of older adults. The connectivity between frontal, parietal, and temporal areas is strengthened, while the intra-area connections in the frontal areas are reduced. Additionally, the network modularity decreases with age.
Article
Engineering, Biomedical
Manuel A. Francisco-Vicencio, Fernando Gongora-Rivera, Xochitl Ortiz-Jimenez, Dulce Martinez-Peon
Summary: Different cognitive models have been created to understand and rehabilitate attention. This study focuses on sustained attention and uses effective connectivity analysis to uncover the dynamics between brain regions. The findings show dominant connections at specific frequencies and present a low-cost tool for assessing cognitive processes and monitoring attention in real-time rehabilitation and educational settings.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Engineering, Biomedical
Lei Zhang, Long Chen, Zhongpeng Wang, Xiuyun Liu, Dong Ming
Summary: This study investigated whether electrically stimulating frontal and parietal regions using dual-site tACS at mu frequency can modulate motor imagery (MI) performance. The results showed that anti-phase stimulation significantly improved event-related desynchronization (ERD) and classification accuracy during complex tasks, while also decreasing event-related functional connectivity within the frontoparietal network. However, no beneficial effects of anti-phase stimulation were found in the simple task.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Neurosciences
Noa Fogelson, Pablo Diaz-Brage
Summary: The study found that PD patients exhibit increased top-down connectivity in the frontal-parietal regions during the processing of implicit predictive stimuli, and they seem to allocate more attentional resources to non-informative standard stimuli compared to controls during the explicit session. These connectivity changes reveal insights into the cognitive deficits associated with processing predictive contextual information in PD patients.
BRAIN AND COGNITION
(2021)
Article
Computer Science, Artificial Intelligence
Jian Zhou, Tiantian Zhao, Yong Xie, Fu Xiao, Lijuan Sun
Summary: This paper proposes an EEG emotion recognition method based on brain connectivity reservoir (BCR) and valence lateralization (VL) to improve the efficiency of Cyber-Physical-Social Systems (CPSS) in providing services for humans. The method establishes an emotion recognition model based on BCR to consider the temporality, nonlinearity, and correlation of EEG signals. Furthermore, a training algorithm based on VL is introduced to enhance the feature representation capability of BCR. Experimental results demonstrate that the proposed method achieves a recognition accuracy of 85.55%, outperforming state-of-the-art methods.
PATTERN RECOGNITION LETTERS
(2022)
Article
Chemistry, Analytical
Leonardo Gongora, Alessia Paglialonga, Alfonso Mastropietro, Giovanna Rizzo, Riccardo Barbieri
Summary: Connectivity among different brain areas is crucial for understanding brain function. This study proposes a method to select the appropriate window size in order to ensure stationarity when studying effective connectivity. The results demonstrate the effectiveness of the proposed method in identifying the influence within the Default Mode Network circuit.
Article
Neurosciences
Jaclyn H. Ford, Sara Y. Kim, Sarah M. Kark, Ryan T. Daley, Jessica D. Payne, Elizabeth A. Kensinger
Summary: This study examines the relationship between stress response, intrinsic amygdala connectivity, and memory performance. The findings suggest that stress response is associated with changes in connectivity and affects the valence of remembered emotional content.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Carlos Alberto Stefano Filho, Romis Attux, Gabriela Castellano
Summary: The use of motor imagery (MI) in motor rehabilitation has potential to enhance traditional treatments, with appropriate training being crucial to benefit from it. Assessing underlying neural changes due to feedback or MI practice remains challenging, with actual neurofeedback impacting functional connectivity (FC) by disrupting common inter-subject patterns. MI practice stimulates visual information processing mechanisms, particularly during resting-state brain activity.
JOURNAL OF NEURAL ENGINEERING
(2021)
Article
Neurosciences
Ignacio Cifre, Maria T. Miller Flores, Lucia Penalba, Jeremi K. Ochab, Dante R. Chialvo
Summary: The center stage of neuro-imaging is currently focused on studying functional correlations between brain regions, which define brain functional networks. This study proposes a new measure of nonlinear dynamic directed functional connectivity across regions of interest, providing directed information of functional correlations and a measure of temporal lags without extensive numerical complications. This approach offers a different and complementary perspective in analyzing brain co-activation patterns.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Mathematical & Computational Biology
Shuang Ma, Chaoyi Dong, Tingting Jia, Pengfei Ma, Zhiyun Xiao, Xiaoyan Chen, Lijie Zhang
Summary: This paper introduces a multichannel correlation analysis method using DTF to identify connectivity between different EEG signal channels and extract network information flow features. The new DTF features, when combined with traditional AR model parameter features, improved the classification accuracy of left- and right-hand motor imagery EEG signals. Experimental results show that the multichannel analysis method is more effective in classification.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Computer Science, Theory & Methods
Weisong Wang, Wenjing Sun
Summary: Emotion is a complex phenomenon that has significant effects on individual decisions. This study analyzed EEG data obtained from 36 participants to determine the effective connectivity between brain sources in different emotional states. The proposed model achieved high accuracy in recognizing positive emotions and has the potential to be integrated with machine learning and neural network methods.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
Article
Behavioral Sciences
Magdalena A. Ferdek, Clementina M. van Rijn, Miroslaw Wyczesany
COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE
(2016)
Article
Obstetrics & Gynecology
Mieke A. W. van Aken, Joukje M. Oosterman, C. M. van Rijn, Magdalena A. Ferdek, Ge S. F. Ruigt, B. W. M. M. Peeters, Didi D. M. Braat, Annerniek W. Nap
FERTILITY AND STERILITY
(2017)
Article
Endocrinology & Metabolism
Mieke van Aken, Joukje Oosterman, Tineke van Rijn, Magdalena Ferdek, Ge Ruigt, Tamas Kozicz, Didi Braat, Ard Peeters, Annemiek Nap
PSYCHONEUROENDOCRINOLOGY
(2018)
Article
Clinical Neurology
Magdalena A. Ferdek, Joukje M. Oosterman, Agnieszka K. Adamczyk, Mieke van Aken, Kelly J. Woudsma, Bernard W. M. M. Peeters, Annemiek Nap, Miroslaw Wyczesany, Clementina M. van Rijn
Article
Neurosciences
Magdalena A. Ferdek, Agnieszka K. Adamczyk, Clementina M. van Rijn, Joukje M. Oosterman, Miroslaw Wyczesany
ACTA NEUROBIOLOGIAE EXPERIMENTALIS
(2019)
