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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wang, Meng-Yun; Yuan, Anzhe; Zhang, Juan; Xiang, Yutao; +1 Authors

    AbstractBrain oscillations are vital to cognitive functions, while disrupted oscillatory activity is linked to various brain disorders. Although high-frequency neural oscillations (> 1 Hz) have been extensively studied in cognition, the neural mechanisms underlying low-frequency hemodynamic oscillations (LFHO) < 1 Hz have not yet been fully explored. One way to examine oscillatory neural dynamics is to use a facial expression (FE) paradigm to induce steady-state visual evoked potentials (SSVEPs), which has been used in electroencephalography studies of high-frequency brain oscillation activity. In this study, LFHO during SSVEP-inducing periodic flickering stimuli presentation were inspected using functional near-infrared spectroscopy (fNIRS), in which hemodynamic responses in the prefrontal cortex were recorded while participants were passively viewing dynamic FEs flickering at 0.2 Hz. The fast Fourier analysis results demonstrated that the power exhibited monochronic peaks at 0.2 Hz across all channels, indicating that the periodic events successfully elicited LFHO in the prefrontal cortex. More importantly, measurement of LFHO can effectively distinguish the brain activation difference between different cognitive conditions, with happy FE presentation showing greater LFHO power than neutral FE presentation. These results demonstrate that stimuli flashing at a given frequency can induce LFHO in the prefrontal cortex, which provides new insights into the cognitive mechanisms involved in slow oscillation.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Visual Computing for Industry, Biomedicine, and Art
    Article . 2020 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Visual Computing for Industry, Biomedicine, and Art
      Article . 2020 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Alisa Berger; Fabian Horst; Sophia Müller; Fabian Steinberg; +2 Authors

    Gait and balance impairments are frequently considered as the most significant concerns among individuals suffering from neurological diseases. Robot-assisted gait training (RAGT) has shown to be a promising neurorehabilitation intervention to improve gait recovery in patients following stroke or brain injury by potentially initiating neuroplastic changes. However, the neurophysiological processes underlying gait recovery through RAGT remain poorly understood. As non-invasive, portable neuroimaging techniques, electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provide new insights regarding the neurophysiological processes occurring during RAGT by measuring different perspectives of brain activity. Due to spatial information about changes in cortical activation patterns and the rapid temporal resolution of bioelectrical changes, more features correlated with brain activation and connectivity can be identified when using fused EEG-fNIRS, thus leading to a detailed understanding of neurophysiological mechanisms underlying motor behavior and impairments due to neurological diseases. Therefore, multi-modal integrations of EEG-fNIRS appear promising for the characterization of neurovascular coupling in brain network dynamics induced by RAGT. In this brief review, we surveyed neuroimaging studies focusing specifically on robotic gait rehabilitation. While previous studies have examined either EEG or fNIRS with respect to RAGT, a multi-modal integration of both approaches is lacking. Based on comparable studies using fused EEG-fNIRS integrations either for guiding non-invasive brain stimulation or as part of brain-machine interface paradigms, the potential of this methodologically combined approach in RAGT is discussed. Future research directions and perspectives for targeted, individualized gait recovery that optimize the outcome and efficiency of RAGT in neurorehabilitation were further derived.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Human N...arrow_drop_down
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Human N...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Article . 2019
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    Authors: El Helou, Nour; Tafflet, Muriel; Berthelot, Geoffroy, C.B.; Tolaini, Julien; +4 Authors

    Objectif: Les objectifs de cette étude sont de décrire la distribution des performances de tous les coureurs des plus grands marathons mondiaux et de déterminer les paramètres environnementaux qui ont l'impact le plus important. Méthodes: Nous avons analysé les résultats de six marathons européens (Paris, Londres, Berlin) et américains (Boston, Chicago, New York) de 2001 à 2010 à travers les performances de 1 791 972 participants (tous les arrivants de chaque course). Les mesures de quatre facteurs environnementaux ont été recueillies pour chacune des 60 courses: température (°C), humidité (%), point de rosée (°C), et pression atmosphérique au niveau de la mer (hPA), ainsi que les concentrations de quatre polluants atmosphériques : NO2-SO2-O3 and PM 10 (µg.m-3). Résultats: Les performances annuelles de chaque course ont une distribution normale avec des paramètres de distribution (moyenne et écart type) qui diffèrent selon les facteurs environnementaux. La température de l'air et la performance sont significativement corrélées à travers un modèle quadratique. Les températures optimales auxquelles sont atteintes les vitesses maximales moyennes des coureurs varient selon le niveau de performance. Lorsque la température augmente au-delà ou diminue en deça de ces optima, la vitesse de course diminue et les taux d'abandons des coureurs augmentent. L'ozone affecte également les performances, mais son effet pourrait être lié à l'augmentation de la température. Les autres paramètres environnementaux n'ont pas d'impact significatif. Conclusions: La quantité importante de données analysées et le modèle développé dans cette étude mettent en évidence l'influence majeure de la température de l'air au-dessus de tout autre paramètre climatique sur les capacités humaine et son adaptation aux conditions climatiques.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ HAL-Inserm; Hyper Ar...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Other literature type . 2011
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Yin Tian; Wei Xu; Huiling Zhang; Kin Y. Tam; +4 Authors

    Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP) appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG) references, namely, AR (average of all recording channels) and reference electrode standardization technique (REST), were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    Article . 2018
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neuroscience
    Article . 2018 . Peer-reviewed
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Article . 2018
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neuroscience
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Article . 2018
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      Frontiers in Neuroscience
      Article . 2018 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Article . 2018
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      Frontiers in Neuroscience
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Meng-Yun Wang; Juan Zhang; Fengmei Lu; Yu-Tao Xiang; +1 Authors

    AbstractBackgroundAccumulating evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is implicated in personality traits. In this study, resting‐state functional near infrared spectroscopy (fNIRS) combined with small‐world analysis was utilized to examine the relationship between the network properties of dlPFC and personality traits.MethodsThirty college students (aged between 20 and 29) were recruited from the University of Macau campus, whose personality scores were accessed with the NEO‐FFT questionnaire. Graph theory combined with resting‐state fNIRS data was used to quantify the network properties of dlPFC, whereas Pearson correlation analysis was performed to generate the relationship between the small‐world indicators and personality scores.ResultsCompared to matched random networks, the resting‐state brain networks exhibited a larger clustering coefficient (Cp, 0.1–0.66), shorter characteristic path length (Lp, 0.1–0.66), and higher global (Eg, 0.1–0.66) and local efficiency (Eloc, 0.1–0.65). In particular, conscientiousness (r = −0.63) and neuroticism (r = 0.40) respectively showed negative and positive correlation with the Lp.ConclusionsThe resting‐state functional brain networks in dlPFC exhibited the small‐world properties. In addition, participants with higher conscientiousness scores showed a shorter Lp.

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    Brain and Behavior
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    Brain and Behavior
    Article . 2018 . Peer-reviewed
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      Brain and Behavior
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      Brain and Behavior
      Article . 2018 . Peer-reviewed
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    Authors: Zhao, Wan; Chen, Xiongying; Zhang, Qiumei; Du, Boqi; +7 Authors

    ZNF804A has now been recognized as a schizophrenia risk gene by multiple genome-wide association studies with its intronic polymorphism rs1344706 being reported as the first genome-wide significant risk variant for schizophrenia. Although the functional impact of this gene is still unknown, rs1344706’s contribution to the functional coupling between the right dorsolateral prefrontal cortex (DLPFC) and the contralateral hippocampal formation (HF) has been reported by several studies. The current study tested whether the right DLPFC-left HF functional coupling showed plasticity during cognitive training (Study I) and whether rs1344706 affected the plasticity (Study II). In Study I, we conducted a randomized controlled trial with 30 subjects receiving 20 sessions of adaptive training on a memory span task (the training group) and 30 subjects practicing on a non-adaptive easy version of the same memory span task for 20 sessions (the control group). All subjects were scanned using fMRI before and after the training. Analyses of resting-state and task-state fMRI data consistently showed that the adaptive memory span training significantly strengthened the right DLPFC-left HF functional coupling. In Study II, we conducted a genetic association study with 101 subjects (combining the data from the training group in Study I with those from an additional subsequent sample of 71 subjects who received the same training and fMRI scans). Results showed that rs1344706 was significantly associated with training-induced changes in functional coupling. Subjects carrying the non-risk allele (C) of rs1344706 showed greater training-induced plasticity than the risk allele (A) homozygotes. These findings expanded our current understanding of the functional impact of the schizophrenia risk variant of ZNF804A gene and suggested that the ZNF804A gene could be used as a prospective target for future antipsychotic drugs and clinical research. Highlights • The working memory training strengthened the right DLPFC-left HF functional coupling. • Rs1344706 was associated with the right DLPFC-left HF functional coupling at pretest. • Rs1344706 impacted the plasticity of the right DLPFC-left HF functional coupling.

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    NeuroImage: Clinical
    Article . 2020
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    NeuroImage: Clinical
    Article . 2020 . Peer-reviewed
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      NeuroImage: Clinical
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    Authors: Jiang Zhang; Xiaohong Lin; Genyu Fu; Liyang Sai; +7 Authors

    AbstractDeception is not a rare occurrence among human behaviors; however, the present brain mapping techniques are insufficient to reveal the neural mechanism of deception under spontaneous or controlled conditions. Interestingly, functional near-infrared spectroscopy (fNIRS) has emerged as a highly promising neuroimaging technique that enables continuous and noninvasive monitoring of changes in blood oxygenation and blood volume in the human brain. In this study, fNIRS was used in combination with complex network theory to extract the attribute features of the functional brain networks underling deception in subjects exhibiting spontaneous or controlled behaviors. Our findings revealed that the small-world networks of the subjects engaged in spontaneous behaviors exhibited greater clustering coefficients, shorter average path lengths, greater average node degrees, and stronger randomness compared with those of subjects engaged in control behaviors. Consequently, we suggest that small-world network topology is capable of distinguishing well between spontaneous and controlled deceptions.

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    Scientific Reports
    Article . 2016 . Peer-reviewed
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      Scientific Reports
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    Authors: Feng-Mei Lu; Yi-Feng Wang; Juan Zhang; Hua-Fu Chen; +1 Authors

    AbstractRecent neuroimaging studies revealed that the dominant frequency of neural oscillations is brain-region-specific and can vary with frequency-specific reorganization of brain networks during cognition. In this study, we examined the dominant frequency in low-frequency neural oscillations represented by oxygenated hemoglobin measurements after the hemodynamic response function (HRF) deconvolution. Twenty-nine healthy college subjects were recruited to perform a serial finger tapping task at the frequency of 0.2 Hz. Functional near-infrared spectroscopy (fNIRS) was applied to record the hemodynamic signals over the primary motor cortex, supplementary motor area (SMA), premotor cortex, and prefrontal area. We then explored the low frequency steady-state brain response (lfSSBR), which was evoked in the motor systems at the fundamental frequency (0.2 Hz) and its harmonics (0.4, 0.6, and 0.8 Hz). In particular, after HRF deconvolution, the lfSSBR at the frequency of 0.4 Hz in the SMA was identified as the dominant frequency. Interestingly, the domain frequency exhibited the correlation with behavior data such as reaction time, indicating that the physiological implication of lfSSBR is related to the brain anatomy, stimulus frequency and cognition. More importantly, the HRF deconvolution showed its capability for recovering signals probably reflecting neural-level events and revealing the physiological meaning of lfSSBR.

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    Scientific Reports
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    Scientific Reports
    Article . 2017
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    Scientific Reports
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    Authors: Lu, Feng-Mei; Liu, Chun-Hong; Lu, Shun-Li; Tang, Li-Rong; +3 Authors

    Insomnia is one of the most common health complaints, with a high prevalence of 30~50% in the general population. In particular, neuroimaging research has revealed that widespread dysfunctions in brain regions involved in hyperarousal are strongly correlated with insomnia. However, whether the topology of the intrinsic connectivity is aberrant in insomnia remains largely unknown. In this study, resting-state functional magnetic resonance imaging (rsfMRI) in conjunction with graph theoretical analysis, was used to construct functional connectivity matrices and to extract the attribute features of the small-world networks in insomnia. We examined the alterations in global and local small-world network properties of the distributed brain regions that are predominantly implicated in the frontostriatal network between 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without insomnia symptoms (NIS). Correlations between the small-world properties and clinical measurements were also generated to identify the differences between the two groups. Both the IS group and the NIS group exhibited a small-worldness topology. Meanwhile, the global topological properties didn't show significant difference between the two groups. By contrast, participants in the IS group showed decreased regional degree and efficiency in the left inferior frontal gyrus (IFG) compared with subjects in the NIS group. More specifically, significantly decreased nodal efficiency in the IFG was found to be negatively associated with insomnia scores, whereas the abnormal changes in nodal betweenness centrality of the right putamen were positively correlated with insomnia scores. Our findings suggested that the aberrant topology of the salience network and frontostriatal connectivity is linked to insomnia, which can serve as an important biomarker for insomnia.

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    Frontiers in Neuroscience
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    Frontiers in Neuroscience
    Article . 2017 . Peer-reviewed
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      Frontiers in Neuroscience
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    Authors: Wan Zhao; Qiumei Zhang; Xiongying Chen; Yang Li; +9 Authors

    AbstractBackgroundThe Arsenic (+3 oxidation state) methyltransferase (AS3MT) gene has been identified as a top risk gene for schizophrenia in several large-scale genome-wide association studies. A variable number tandem repeat (VNTR) of this gene is the most significant expression quantitative trait locus, but its role in brain activity in vivo is still unknown.MethodsWe first performed a functional magnetic resonance imaging (fMRI) scan of 101 healthy subjects during a memory span task, trained all subjects on an adaptive memory span task for 1 month, and finally performed another fMRI scan after the training. After excluding subjects with excessive head movements for one or more scanning sessions, data from 93 subjects were included in the final analyses.ResultsThe VNTR was significantly associated with both baseline brain activation and training-induced changes in multiple regions including the prefrontal cortex and the anterior and posterior cingulate cortex. Additionally, it was associated with baseline brain activation in the striatum and the parietal cortex. All these results were corrected based on the family-wise error rate method across the whole brain at the peak level.ConclusionsThis study sheds light on the role of AS3MT gene variants in neural plasticity related to memory span training.

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    Psychological Medicine
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    Psychological Medicine
    Article . 2020 . Peer-reviewed
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      Psychological Medicine
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      Psychological Medicine
      Article . 2020 . Peer-reviewed
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    Authors: Wang, Meng-Yun; Yuan, Anzhe; Zhang, Juan; Xiang, Yutao; +1 Authors

    AbstractBrain oscillations are vital to cognitive functions, while disrupted oscillatory activity is linked to various brain disorders. Although high-frequency neural oscillations (> 1 Hz) have been extensively studied in cognition, the neural mechanisms underlying low-frequency hemodynamic oscillations (LFHO) < 1 Hz have not yet been fully explored. One way to examine oscillatory neural dynamics is to use a facial expression (FE) paradigm to induce steady-state visual evoked potentials (SSVEPs), which has been used in electroencephalography studies of high-frequency brain oscillation activity. In this study, LFHO during SSVEP-inducing periodic flickering stimuli presentation were inspected using functional near-infrared spectroscopy (fNIRS), in which hemodynamic responses in the prefrontal cortex were recorded while participants were passively viewing dynamic FEs flickering at 0.2 Hz. The fast Fourier analysis results demonstrated that the power exhibited monochronic peaks at 0.2 Hz across all channels, indicating that the periodic events successfully elicited LFHO in the prefrontal cortex. More importantly, measurement of LFHO can effectively distinguish the brain activation difference between different cognitive conditions, with happy FE presentation showing greater LFHO power than neutral FE presentation. These results demonstrate that stimuli flashing at a given frequency can induce LFHO in the prefrontal cortex, which provides new insights into the cognitive mechanisms involved in slow oscillation.

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    Visual Computing for Industry, Biomedicine, and Art
    Article . 2020 . Peer-reviewed
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      Visual Computing for Industry, Biomedicine, and Art
      Article . 2020 . Peer-reviewed
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    Authors: Alisa Berger; Fabian Horst; Sophia Müller; Fabian Steinberg; +2 Authors

    Gait and balance impairments are frequently considered as the most significant concerns among individuals suffering from neurological diseases. Robot-assisted gait training (RAGT) has shown to be a promising neurorehabilitation intervention to improve gait recovery in patients following stroke or brain injury by potentially initiating neuroplastic changes. However, the neurophysiological processes underlying gait recovery through RAGT remain poorly understood. As non-invasive, portable neuroimaging techniques, electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provide new insights regarding the neurophysiological processes occurring during RAGT by measuring different perspectives of brain activity. Due to spatial information about changes in cortical activation patterns and the rapid temporal resolution of bioelectrical changes, more features correlated with brain activation and connectivity can be identified when using fused EEG-fNIRS, thus leading to a detailed understanding of neurophysiological mechanisms underlying motor behavior and impairments due to neurological diseases. Therefore, multi-modal integrations of EEG-fNIRS appear promising for the characterization of neurovascular coupling in brain network dynamics induced by RAGT. In this brief review, we surveyed neuroimaging studies focusing specifically on robotic gait rehabilitation. While previous studies have examined either EEG or fNIRS with respect to RAGT, a multi-modal integration of both approaches is lacking. Based on comparable studies using fused EEG-fNIRS integrations either for guiding non-invasive brain stimulation or as part of brain-machine interface paradigms, the potential of this methodologically combined approach in RAGT is discussed. Future research directions and perspectives for targeted, individualized gait recovery that optimize the outcome and efficiency of RAGT in neurorehabilitation were further derived.

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      Article . 2019
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    Authors: El Helou, Nour; Tafflet, Muriel; Berthelot, Geoffroy, C.B.; Tolaini, Julien; +4 Authors

    Objectif: Les objectifs de cette étude sont de décrire la distribution des performances de tous les coureurs des plus grands marathons mondiaux et de déterminer les paramètres environnementaux qui ont l'impact le plus important. Méthodes: Nous avons analysé les résultats de six marathons européens (Paris, Londres, Berlin) et américains (Boston, Chicago, New York) de 2001 à 2010 à travers les performances de 1 791 972 participants (tous les arrivants de chaque course). Les mesures de quatre facteurs environnementaux ont été recueillies pour chacune des 60 courses: température (°C), humidité (%), point de rosée (°C), et pression atmosphérique au niveau de la mer (hPA), ainsi que les concentrations de quatre polluants atmosphériques : NO2-SO2-O3 and PM 10 (µg.m-3). Résultats: Les performances annuelles de chaque course ont une distribution normale avec des paramètres de distribution (moyenne et écart type) qui diffèrent selon les facteurs environnementaux. La température de l'air et la performance sont significativement corrélées à travers un modèle quadratique. Les températures optimales auxquelles sont atteintes les vitesses maximales moyennes des coureurs varient selon le niveau de performance. Lorsque la température augmente au-delà ou diminue en deça de ces optima, la vitesse de course diminue et les taux d'abandons des coureurs augmentent. L'ozone affecte également les performances, mais son effet pourrait être lié à l'augmentation de la température. Les autres paramètres environnementaux n'ont pas d'impact significatif. Conclusions: La quantité importante de données analysées et le modèle développé dans cette étude mettent en évidence l'influence majeure de la température de l'air au-dessus de tout autre paramètre climatique sur les capacités humaine et son adaptation aux conditions climatiques.

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    Authors: Yin Tian; Wei Xu; Huiling Zhang; Kin Y. Tam; +4 Authors

    Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP) appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG) references, namely, AR (average of all recording channels) and reference electrode standardization technique (REST), were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

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    Article . 2018
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    Frontiers in Neuroscience
    Article . 2018 . Peer-reviewed
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      Frontiers in Neuroscience
      Article . 2018 . Peer-reviewed
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    Authors: Meng-Yun Wang; Juan Zhang; Fengmei Lu; Yu-Tao Xiang; +1 Authors

    AbstractBackgroundAccumulating evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is implicated in personality traits. In this study, resting‐state functional near infrared spectroscopy (fNIRS) combined with small‐world analysis was utilized to examine the relationship between the network properties of dlPFC and personality traits.MethodsThirty college students (aged between 20 and 29) were recruited from the University of Macau campus, whose personality scores were accessed with the NEO‐FFT questionnaire. Graph theory combined with resting‐state fNIRS data was used to quantify the network properties of dlPFC, whereas Pearson correlation analysis was performed to generate the relationship between the small‐world indicators and personality scores.ResultsCompared to matched random networks, the resting‐state brain networks exhibited a larger clustering coefficient (Cp, 0.1–0.66), shorter characteristic path length (Lp, 0.1–0.66), and higher global (Eg, 0.1–0.66) and local efficiency (Eloc, 0.1–0.65). In particular, conscientiousness (r = −0.63) and neuroticism (r = 0.40) respectively showed negative and positive correlation with the Lp.ConclusionsThe resting‐state functional brain networks in dlPFC exhibited the small‐world properties. In addition, participants with higher conscientiousness scores showed a shorter Lp.

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    Brain and Behavior
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    Brain and Behavior
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      Brain and Behavior
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    Authors: Zhao, Wan; Chen, Xiongying; Zhang, Qiumei; Du, Boqi; +7 Authors

    ZNF804A has now been recognized as a schizophrenia risk gene by multiple genome-wide association studies with its intronic polymorphism rs1344706 being reported as the first genome-wide significant risk variant for schizophrenia. Although the functional impact of this gene is still unknown, rs1344706’s contribution to the functional coupling between the right dorsolateral prefrontal cortex (DLPFC) and the contralateral hippocampal formation (HF) has been reported by several studies. The current study tested whether the right DLPFC-left HF functional coupling showed plasticity during cognitive training (Study I) and whether rs1344706 affected the plasticity (Study II). In Study I, we conducted a randomized controlled trial with 30 subjects receiving 20 sessions of adaptive training on a memory span task (the training group) and 30 subjects practicing on a non-adaptive easy version of the same memory span task for 20 sessions (the control group). All subjects were scanned using fMRI before and after the training. Analyses of resting-state and task-state fMRI data consistently showed that the adaptive memory span training significantly strengthened the right DLPFC-left HF functional coupling. In Study II, we conducted a genetic association study with 101 subjects (combining the data from the training group in Study I with those from an additional subsequent sample of 71 subjects who received the same training and fMRI scans). Results showed that rs1344706 was significantly associated with training-induced changes in functional coupling. Subjects carrying the non-risk allele (C) of rs1344706 showed greater training-induced plasticity than the risk allele (A) homozygotes. These findings expanded our current understanding of the functional impact of the schizophrenia risk variant of ZNF804A gene and suggested that the ZNF804A gene could be used as a prospective target for future antipsychotic drugs and clinical research. Highlights • The working memory training strengthened the right DLPFC-left HF functional coupling. • Rs1344706 was associated with the right DLPFC-left HF functional coupling at pretest. • Rs1344706 impacted the plasticity of the right DLPFC-left HF functional coupling.

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    NeuroImage: Clinical
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    NeuroImage: Clinical
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      NeuroImage: Clinical
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    Authors: Jiang Zhang; Xiaohong Lin; Genyu Fu; Liyang Sai; +7 Authors

    AbstractDeception is not a rare occurrence among human behaviors; however, the present brain mapping techniques are insufficient to reveal the neural mechanism of deception under spontaneous or controlled conditions. Interestingly, functional near-infrared spectroscopy (fNIRS) has emerged as a highly promising neuroimaging technique that enables continuous and noninvasive monitoring of changes in blood oxygenation and blood volume in the human brain. In this study, fNIRS was used in combination with complex network theory to extract the attribute features of the functional brain networks underling deception in subjects exhibiting spontaneous or controlled behaviors. Our findings revealed that the small-world networks of the subjects engaged in spontaneous behaviors exhibited greater clustering coefficients, shorter average path lengths, greater average node degrees, and stronger randomness compared with those of subjects engaged in control behaviors. Consequently, we suggest that small-world network topology is capable of distinguishing well between spontaneous and controlled deceptions.

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    Scientific Reports
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    Authors: Feng-Mei Lu; Yi-Feng Wang; Juan Zhang; Hua-Fu Chen; +1 Authors

    AbstractRecent neuroimaging studies revealed that the dominant frequency of neural oscillations is brain-region-specific and can vary with frequency-specific reorganization of brain networks during cognition. In this study, we examined the dominant frequency in low-frequency neural oscillations represented by oxygenated hemoglobin measurements after the hemodynamic response function (HRF) deconvolution. Twenty-nine healthy college subjects were recruited to perform a serial finger tapping task at the frequency of 0.2 Hz. Functional near-infrared spectroscopy (fNIRS) was applied to record the hemodynamic signals over the primary motor cortex, supplementary motor area (SMA), premotor cortex, and prefrontal area. We then explored the low frequency steady-state brain response (lfSSBR), which was evoked in the motor systems at the fundamental frequency (0.2 Hz) and its harmonics (0.4, 0.6, and 0.8 Hz). In particular, after HRF deconvolution, the lfSSBR at the frequency of 0.4 Hz in the SMA was identified as the dominant frequency. Interestingly, the domain frequency exhibited the correlation with behavior data such as reaction time, indicating that the physiological implication of lfSSBR is related to the brain anatomy, stimulus frequency and cognition. More importantly, the HRF deconvolution showed its capability for recovering signals probably reflecting neural-level events and revealing the physiological meaning of lfSSBR.

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    Authors: Lu, Feng-Mei; Liu, Chun-Hong; Lu, Shun-Li; Tang, Li-Rong; +3 Authors

    Insomnia is one of the most common health complaints, with a high prevalence of 30~50% in the general population. In particular, neuroimaging research has revealed that widespread dysfunctions in brain regions involved in hyperarousal are strongly correlated with insomnia. However, whether the topology of the intrinsic connectivity is aberrant in insomnia remains largely unknown. In this study, resting-state functional magnetic resonance imaging (rsfMRI) in conjunction with graph theoretical analysis, was used to construct functional connectivity matrices and to extract the attribute features of the small-world networks in insomnia. We examined the alterations in global and local small-world network properties of the distributed brain regions that are predominantly implicated in the frontostriatal network between 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without insomnia symptoms (NIS). Correlations between the small-world properties and clinical measurements were also generated to identify the differences between the two groups. Both the IS group and the NIS group exhibited a small-worldness topology. Meanwhile, the global topological properties didn't show significant difference between the two groups. By contrast, participants in the IS group showed decreased regional degree and efficiency in the left inferior frontal gyrus (IFG) compared with subjects in the NIS group. More specifically, significantly decreased nodal efficiency in the IFG was found to be negatively associated with insomnia scores, whereas the abnormal changes in nodal betweenness centrality of the right putamen were positively correlated with insomnia scores. Our findings suggested that the aberrant topology of the salience network and frontostriatal connectivity is linked to insomnia, which can serve as an important biomarker for insomnia.

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    Frontiers in Neuroscience
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    Frontiers in Neuroscience
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      Frontiers in Neuroscience
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    Authors: Wan Zhao; Qiumei Zhang; Xiongying Chen; Yang Li; +9 Authors

    AbstractBackgroundThe Arsenic (+3 oxidation state) methyltransferase (AS3MT) gene has been identified as a top risk gene for schizophrenia in several large-scale genome-wide association studies. A variable number tandem repeat (VNTR) of this gene is the most significant expression quantitative trait locus, but its role in brain activity in vivo is still unknown.MethodsWe first performed a functional magnetic resonance imaging (fMRI) scan of 101 healthy subjects during a memory span task, trained all subjects on an adaptive memory span task for 1 month, and finally performed another fMRI scan after the training. After excluding subjects with excessive head movements for one or more scanning sessions, data from 93 subjects were included in the final analyses.ResultsThe VNTR was significantly associated with both baseline brain activation and training-induced changes in multiple regions including the prefrontal cortex and the anterior and posterior cingulate cortex. Additionally, it was associated with baseline brain activation in the striatum and the parietal cortex. All these results were corrected based on the family-wise error rate method across the whole brain at the peak level.ConclusionsThis study sheds light on the role of AS3MT gene variants in neural plasticity related to memory span training.

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    Psychological Medicine
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    Psychological Medicine
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