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Kim E, Yun SJ, Oh BM, Seo HG. Impact of Electric Field Magnitude in the Left Dorsolateral Prefrontal Cortex on Changes in Intrinsic Functional Connectivity Using Transcranial Direct Current Stimulation: A Randomized Crossover Study. J Neurosci Res 2024; 102:e25378. [PMID: 39225477 DOI: 10.1002/jnr.25378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 08/06/2024] [Accepted: 08/10/2024] [Indexed: 09/04/2024]
Abstract
This study investigated whether the electric field magnitude (E-field) delivered to the left dorsolateral prefrontal cortex (L-DLPFC) changes resting-state brain activity and the L-DLPFC resting-state functional connectivity (rsFC), given the variability in tDCS response and lack of understanding of how rsFC changes. Twenty-one healthy participants received either 2 mA anodal or sham tDCS targeting the L-DLPFC for 10 min. Brain imaging was conducted before and after stimulation. The fractional amplitude of low-frequency fluctuation (fALFF), reflecting resting brain activity, and the L-DLPFC rsFC were analyzed to investigate the main effect of tDCS, main effect of time, and interaction effects. The E-field was estimated by modeling tDCS-induced individual electric fields and correlated with fALFF and L-DLPFC rsFC. Anodal tDCS increased fALFF in the left rostral middle frontal area and decreased fALFF in the midline frontal area (FWE p < 0.050), whereas sham induced no changes. Overall rsFC decreased after sham (positive and negative connectivity, p = 0.001 and 0.020, respectively), with modest and nonsignificant changes after anodal tDCS (p = 0.063 and 0.069, respectively). No significant differences in local rsFC were observed among the conditions. Correlations were observed between the E-field and rsFC changes in the L-DLPFC (r = 0.385, p = 0.115), left inferior parietal area (r = 0.495, p = 0.037), and right lateral visual area (r = 0.683, p = 0.002). Single-session tDCS induced resting brain activity changes and may help maintain overall rsFC. The E-field in the L-DLPFC is associated with rsFC changes in both proximal and distally connected brain regions to the L-DLPFC.
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Affiliation(s)
- Eunkyung Kim
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Seo Jung Yun
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Human Systems Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Byung-Mo Oh
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute on Aging, Seoul National University, Seoul, Korea
| | - Han Gil Seo
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
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Huang BK, Zhou JH, Deng Y, Li CH, Ning BL, Ye ZY, Huang XC, Zhao MM, Dong D, Liu M, Zhang DL, Fu WB. Perceived stress and brain connectivity in subthreshold depression: Insights from eyes-closed and eyes-open states. Brain Res 2024; 1838:148947. [PMID: 38657887 DOI: 10.1016/j.brainres.2024.148947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/09/2024] [Accepted: 04/16/2024] [Indexed: 04/26/2024]
Abstract
Perceived stress is an acknowledged risk factor for subthreshold depression (StD), and fluctuations in perceived stress are thought to disrupt the harmony of brain networks essential for emotional and cognitive functioning. This study aimed to elucidate the relationship between eye-open (EO) and eye-closed (EC) states, perceived stress, and StD. We recruited 27 individuals with StD and 33 healthy controls, collecting resting state fMRI data under both EC and EO conditions. We combined intrinsic connectivity and seed-based functional connectivity analyses to construct the functional network and explore differences between EC and EO conditions. Graph theory analysis revealed weakened connectivity strength in the right superior frontal gyrus (SFG) and right median cingulate and paracingulate gyrus (MCC) among participants with StD, suggesting an important role for these regions in the stress-related emotions dysregulation. Notably, altered SFG connectivity was observed to significantly relate to perceived stress levels in StD, and the SFG connection emerges as a neural mediator potentially influencing the relationship between perceived stress and StD. These findings highlight the role of SFG and MCC in perceived stress and suggest that understanding EC and EO states in relation to these regions is important in the neurobiological framework of StD. This may offer valuable perspectives for early prevention and intervention strategies in mental health disorders.
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Affiliation(s)
- Bin-Kun Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Jun-He Zhou
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; Department of Acupuncture and Moxibustion, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Ying Deng
- The Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Chang-Hong Li
- College of Teacher Education, Guangdong University of Education, Guangzhou 510303, China
| | - Bai-Le Ning
- Department of Acupuncture and Moxibustion, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Zi-Yu Ye
- Acupuncture and Rehabilitation Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Xi-Chang Huang
- The Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Mi-Mi Zhao
- Acupuncture and Rehabilitation Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Dian Dong
- Acupuncture and Rehabilitation Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Ming Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - De-Long Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China.
| | - Wen-Bin Fu
- Department of Acupuncture and Moxibustion, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China.
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Ingram BT, Mayhew SD, Bagshaw AP. Brain state dynamics differ between eyes open and eyes closed rest. Hum Brain Mapp 2024; 45:e26746. [PMID: 38989618 PMCID: PMC11237880 DOI: 10.1002/hbm.26746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 04/25/2024] [Accepted: 05/08/2024] [Indexed: 07/12/2024] Open
Abstract
The human brain exhibits spatio-temporally complex activity even in the absence of external stimuli, cycling through recurring patterns of activity known as brain states. Thus far, brain state analysis has primarily been restricted to unimodal neuroimaging data sets, resulting in a limited definition of state and a poor understanding of the spatial and temporal relationships between states identified from different modalities. Here, we applied hidden Markov model (HMM) to concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI) eyes open (EO) and eyes closed (EC) resting-state data, training models on the EEG and fMRI data separately, and evaluated the models' ability to distinguish dynamics between the two rest conditions. Additionally, we employed a general linear model approach to identify the BOLD correlates of the EEG-defined states to investigate whether the fMRI data could be used to improve the spatial definition of the EEG states. Finally, we performed a sliding window-based analysis on the state time courses to identify slower changes in the temporal dynamics, and then correlated these time courses across modalities. We found that both models could identify expected changes during EC rest compared to EO rest, with the fMRI model identifying changes in the activity and functional connectivity of visual and attention resting-state networks, while the EEG model correctly identified the canonical increase in alpha upon eye closure. In addition, by using the fMRI data, it was possible to infer the spatial properties of the EEG states, resulting in BOLD correlation maps resembling canonical alpha-BOLD correlations. Finally, the sliding window analysis revealed unique fractional occupancy dynamics for states from both models, with a selection of states showing strong temporal correlations across modalities. Overall, this study highlights the efficacy of using HMMs for brain state analysis, confirms that multimodal data can be used to provide more in-depth definitions of state and demonstrates that states defined across different modalities show similar temporal dynamics.
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Affiliation(s)
- Brandon T. Ingram
- Centre for Human Brain Health, School of PsychologyUniversity of BirminghamBirminghamUK
| | - Stephen D. Mayhew
- Institute of Health and NeurodevelopmentSchool of Psychology, Aston UniversityBirminghamUK
| | - Andrew P. Bagshaw
- Centre for Human Brain Health, School of PsychologyUniversity of BirminghamBirminghamUK
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Wang Y, Zeng P, Gu Z, Liu H, Han S, Liu X, Huang X, Shao L, Tao Y. Objective Neurophysiological Indices for the Assessment of Chronic Tinnitus Based on EEG Microstate Parameters. IEEE Trans Neural Syst Rehabil Eng 2024; 32:983-993. [PMID: 38376977 DOI: 10.1109/tnsre.2024.3367982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Chronic tinnitus is highly prevalent but lacks precise diagnostic or effective therapeutic standards. Its onset and treatment mechanisms remain unclear, and there is a shortage of objective assessment methods. We aim to identify abnormal neural activity and reorganization in tinnitus patients and reveal potential neurophysiological markers for objectively evaluating tinnitus. By way of analyzing EEG microstates, comparing metrics under three resting states (OE, CE, and OECEm) between tinnitus sufferers and controls, and correlating them with tinnitus symptoms. This study reflected specific changes in the EEG microstates of tinnitus patients across multiple resting states, as well as inconsistent correlations with tinnitus symptoms. Microstate parameters were significantly different when patients were in OE and CE states. Specifically, the occurrence of Microstate A and the transition probabilities (TP) from other Microstates to A increased significantly, particularly in the CE state (32-37%, p ≤ 0.05 ); and both correlated positively with the tinnitus intensity. Nevertheless, under the OECEm state, increases were mainly observed in the duration, coverage, and occurrence of Microstate B (15-47%, ), which negatively correlated with intensity ( [Formula: see text]-0.513, ). Additionally, TPx between Microstates C and D were significantly reduced and positively correlated with HDAS levels ( [Formula: see text] 0.548, ). Furthermore, parameters of Microstate D also correlated with THI grades ( [Formula: see text]-0.576, ). The findings of this study could offer compelling evidence for central neural reorganization associated with chronic tinnitus. EEG microstate parameters that correlate with tinnitus symptoms could serve as neurophysiological markers, contributing to future research on the objective assessment of tinnitus.
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Zhang Y, Han X, Ge X, Xu T, Wang Y, Mu J, Liu F. Modular brain network in volitional eyes closing: enhanced integration with a marked impact on hubs. Cereb Cortex 2024; 34:bhad464. [PMID: 38044477 DOI: 10.1093/cercor/bhad464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/12/2023] [Accepted: 11/13/2023] [Indexed: 12/05/2023] Open
Abstract
Volitional eyes closing would shift brain's information processing modes from the "exteroceptive" to "interoceptive" state. This transition induced by the eyes closing is underpinned by a large-scale reconfiguration of brain network, which is still not fully comprehended. Here, we investigated the eyes-closing-relevant network reconfiguration by examining the functional integration among intrinsic modules. Our investigation utilized a publicly available dataset with 48 subjects being scanned in both eyes closed and eyes open conditions. It was found that the modular integration was significantly enhanced during the eyes closing, including lower modularity index, higher participation coefficient, less provincial hubs, and more connector hubs. Moreover, the eyes-closing-enhanced integration was particularly noticeable in the hubs of network, mainly located in the default-mode network. Finally, the hub-dominant modular enhancement was positively correlated to the eyes-closing-reduced entropy of BOLD signal, suggesting a close connection to the diminished consciousness of individuals. Collectively, our findings strongly suggested that the enhanced modular integration with substantially reorganized hubs characterized the large-scale cortical underpinning of the volitional eyes closing.
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Affiliation(s)
- Yi Zhang
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Xiao Han
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Xuelian Ge
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Tianyong Xu
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Yanjie Wang
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Jiali Mu
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Fan Liu
- Bio-X Laboratory, Department of Physics, Zhejiang University, Hangzhou 310027, China
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Ma M, Li Y, Shao Y, Weng X. Effect of total sleep deprivation on effective EEG connectivity for young male in resting-state networks in different eye states. Front Neurosci 2023; 17:1204457. [PMID: 37928738 PMCID: PMC10620317 DOI: 10.3389/fnins.2023.1204457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Background Many studies have investigated the effect of total sleep deprivation (TSD) on resting-state functional networks, especially the default mode network (DMN) and sensorimotor network (SMN), using functional connectivity. While it is known that the activities of these networks differ based on eye state, it remains unclear how TSD affects them in different eye states. Therefore, we aimed to examine the effect of TSD on DMN and SMN in different eye states using effective functional connectivity via isolated effective coherence (iCoh) in exact low-resolution brain electromagnetic tomography (eLORETA). Methods Resting-state electroencephalogram (EEG) signals were collected from 24 male college students, and each participant completed a psychomotor vigilance task (PVT) while behavioral data were acquired. Each participant underwent 36-h TSD, and the data were acquired in two sleep-deprivation times (rested wakefulness, RW: 0 h; and TSD: 36 h) and two eye states (eyes closed, EC; and eyes open, EO). Changes in neural oscillations and effective connectivity were compared based on paired t-test. Results The behavioral results showed that PVT reaction time was significantly longer in TSD compared with that of RW. The EEG results showed that in the EO state, the activity of high-frequency bands in the DMN and SMN were enhanced compared to those of the EC state. Furthermore, when compared with the DMN and SMN of RW, in TSD, the activity of DMN was decreased, and SMN was increased. Moreover, the changed effective connectivity in the DMN and SMN after TSD was positively correlated with an increased PVT reaction time. In addition, the effective connectivity in the different network (EO-EC) of the SMN was reduced in the β band after TSD compared with that of RW. Conclusion These findings indicate that TSD impairs alertness and sensory information input in the SMN to a greater extent in an EO than in an EC state.
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Affiliation(s)
- Mengke Ma
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yutong Li
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Xiechuan Weng
- Department of Neuroscience, Beijing Institute of Basic Medical Sciences, Beijing, China
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Seifpour S, Šatka A. Tensor Decomposition Analysis of Longitudinal EEG Signals Reveals Differential Oscillatory Dynamics in Eyes-Closed and Eyes-Open Motor Imagery BCI: A Case Report. Brain Sci 2023; 13:1013. [PMID: 37508946 PMCID: PMC10377314 DOI: 10.3390/brainsci13071013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/30/2023] Open
Abstract
Functional dissociation of brain neural activity induced by opening or closing the eyes has been well established. However, how the temporal dynamics of the underlying neuronal modulations differ between these eye conditions during movement-related behaviours is less known. Using a robotic-assisted motor imagery brain-computer interface (MI BCI), we measured neural activity over the motor regions with electroencephalography (EEG) in a stroke survivor during his longitudinal rehabilitation training. We investigated lateralized oscillatory sensorimotor rhythm modulations while the patient imagined moving his hemiplegic hand with closed and open eyes to control an external robotic splint. In order to precisely identify the main profiles of neural activation affected by MI with eyes-open (MIEO) and eyes-closed (MIEC), a data-driven approach based on parallel factor analysis (PARAFAC) tensor decomposition was employed. Using the proposed framework, a set of narrow-band, subject-specific sensorimotor rhythms was identified; each of them had its own spatial and time signature. When MIEC trials were compared with MIEO trials, three key narrow-band rhythms whose peak frequencies centred at ∼8.0 Hz, ∼11.5 Hz, and ∼15.5 Hz, were identified with differently modulated oscillatory dynamics during movement preparation, initiation, and completion time frames. Furthermore, we observed that lower and higher sensorimotor oscillations represent different functional mechanisms within the MI paradigm, reinforcing the hypothesis that rhythmic activity in the human sensorimotor system is dissociated. Leveraging PARAFAC, this study achieves remarkable precision in estimating latent sensorimotor neural substrates, aiding the investigation of the specific functional mechanisms involved in the MI process.
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Affiliation(s)
- Saman Seifpour
- RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
- Institute of Measurement Science, Slovak Academy of Sciences, Dubravska cesta 9, 84104 Bratislava, Slovakia
| | - Alexander Šatka
- Institute of Measurement Science, Slovak Academy of Sciences, Dubravska cesta 9, 84104 Bratislava, Slovakia
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Zhang X, Zang Z. Evaluate the efficacy and reliability of functional gradients in within-subject designs. Hum Brain Mapp 2023; 44:2336-2344. [PMID: 36661209 PMCID: PMC10028665 DOI: 10.1002/hbm.26213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/05/2023] [Accepted: 01/09/2023] [Indexed: 01/21/2023] Open
Abstract
The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain-general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between-group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within-subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting-state conditions from 145 participants. We found significantly lower within-network dispersion of visual network (VN) (p = 7.3 × 10-4 ) as well as sensorimotor network (SMN) (p = 1 × 10-5 ) and between-network dispersion of VN (p = 2.3 × 10-4 ) under EC than EO, while frontoparietal network (p = 9.2 × 10-4 ) showed significantly higher between-network dispersion during EC than EO. Test-retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within-network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting-state conditions, such that this method could be generalized to other within-subject designs.
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Affiliation(s)
- Xiaolong Zhang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing, China
| | - Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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Wang Y, Li J, Zeng L, Wang H, Yang T, Shao Y, Weng X. Open Eyes Increase Neural Oscillation and Enhance Effective Brain Connectivity of the Default Mode Network: Resting-State Electroencephalogram Research. Front Neurosci 2022; 16:861247. [PMID: 35573310 PMCID: PMC9092973 DOI: 10.3389/fnins.2022.861247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 04/05/2022] [Indexed: 11/13/2022] Open
Abstract
The default mode network (DMN) has a unique activity pattern in the resting brain. Studies on resting-state brain activity are helpful to identify various brain dynamic characteristics of patients with mental diseases and those of healthy people. The brain produces a series of changes in different eye states. However, the relationship between eye states and the DMN, which is closely related to the resting state, has not been widely examined. This study recruited 42 healthy students aged 17–22. Participants completed the Profile of Mood States questionnaire. Thereafter, the electroencephalogram data was collected with the patients’ eyes open and closed. Changes in neural oscillation and the DMN’s information transmission during different eye openness states were compared. The results showed that the neural oscillation activities of the parietal-occipital network such as the superior parietal lobule and precuneus were significantly enhanced in the eyes open state. In addition, the effective connectivity within the DMN was enhanced during opened eyes, especially from the left precuneus to the left posterior cingulate cortex, and this connectivity was negatively correlated with the Vigor-Activity mood state in the eyes open state. The activity of the DMN in the resting-state is regulated by eye states, which may relate to mood and emotional perception.
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Affiliation(s)
- Yi Wang
- Department of Physical Education, Renmin University of China, Beijing, China.,School of Life Sciences and Technology, Harbin Institute of Technology, Harbin, China
| | - Jialu Li
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Lingjing Zeng
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Haiteng Wang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Tianyi Yang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
| | - Xiechuan Weng
- Beijing Institute of Basic Medical Sciences, Beijing, China
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Guglielmini S, Bopp G, Marcar VL, Scholkmann F, Wolf M. Systemic physiology augmented functional near-infrared spectroscopy hyperscanning: a first evaluation investigating entrainment of spontaneous activity of brain and body physiology between subjects. NEUROPHOTONICS 2022; 9:026601. [PMID: 35449706 PMCID: PMC9016073 DOI: 10.1117/1.nph.9.2.026601] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 03/18/2022] [Indexed: 05/27/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) enables measuring the brain activity of two subjects while they interact, i.e., the hyperscanning approach. Aim: In our exploratory study, we extended classical fNIRS hyperscanning by adding systemic physiological measures to obtain systemic physiology augmented fNIRS (SPA-fNIRS) hyperscanning while blocking and not blocking the visual communication between the subjects. This approach enables access brain-to-brain, brain-to-body, and body-to-body coupling between the subjects simultaneously. Approach: Twenty-four pairs of subjects participated in the experiment. The paradigm consisted of two subjects that sat in front of each other and had their eyes closed for 10 min, followed by a phase of 10 min where they made eye contact. Brain and body activity was measured continuously by SPA-fNIRS. Results: Our study shows that making eye contact for a prolonged time causes significant changes in brain-to-brain, brain-to-body, and body-to-body coupling, indicating that eye contact is followed by entrainment of the physiology between subjects. Subjects that knew each other generally showed a larger trend to change between the two conditions. Conclusions: The main point of this study is to introduce a new framework to investigate brain-to-brain, body-to-body, and brain-to-body coupling through a simple social experimental paradigm. The study revealed that eye contact leads to significant synchronization of spontaneous activity of the brain and body physiology. Our study is the first that employed the SPA-fNIRS approach and showed its usefulness to investigate complex interpersonal physiological changes.
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Affiliation(s)
- Sabino Guglielmini
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
| | - Gino Bopp
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
| | - Valentine L. Marcar
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
- University Hospital Zürich, Comprehensive Cancer Center Zürich, Zürich, Switzerland
| | - Felix Scholkmann
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
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Guerreiro MJS, Linke M, Lingareddy S, Kekunnaya R, Röder B. The effect of congenital blindness on resting-state functional connectivity revisited. Sci Rep 2021; 11:12433. [PMID: 34127748 PMCID: PMC8203782 DOI: 10.1038/s41598-021-91976-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/03/2021] [Indexed: 02/05/2023] Open
Abstract
Lower resting-state functional connectivity (RSFC) between 'visual' and non-'visual' neural circuits has been reported as a hallmark of congenital blindness. In sighted individuals, RSFC between visual and non-visual brain regions has been shown to increase during rest with eyes closed relative to rest with eyes open. To determine the role of visual experience on the modulation of RSFC by resting state condition-as well as to evaluate the effect of resting state condition on group differences in RSFC-, we compared RSFC between visual and somatosensory/auditory regions in congenitally blind individuals (n = 9) and sighted participants (n = 9) during eyes open and eyes closed conditions. In the sighted group, we replicated the increase of RSFC between visual and non-visual areas during rest with eyes closed relative to rest with eyes open. This was not the case in the congenitally blind group, resulting in a lower RSFC between 'visual' and non-'visual' circuits relative to sighted controls only in the eyes closed condition. These results indicate that visual experience is necessary for the modulation of RSFC by resting state condition and highlight the importance of considering whether sighted controls should be tested with eyes open or closed in studies of functional brain reorganization as a consequence of blindness.
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Affiliation(s)
- Maria J S Guerreiro
- Biological Psychology and Neuropsychology, Institute for Psychology, University of Hamburg, Von-Melle-Park 11, 20146, Hamburg, Germany.
- Biological Psychology, Department of Psychology, Carl Von Ossietzky University of Oldenburg, 26111, Oldenburg, Germany.
| | - Madita Linke
- Biological Psychology and Neuropsychology, Institute for Psychology, University of Hamburg, Von-Melle-Park 11, 20146, Hamburg, Germany
| | - Sunitha Lingareddy
- Department of Radiology, Lucid Medical Diagnostics, Banjara Hills, Hyderabad, Telengana, 500082, India
| | - Ramesh Kekunnaya
- Child Sight Institute, Jasti V. Ramanamma Children's Eye Care Center, Department of Pediatric Ophthalmology, Strabismus, and Neuro-Ophthalmology, L. V. Prasad Eye Institute, Kallam Anji Reddy Campus, Hyderabad, Telengana, 500034, India
| | - Brigitte Röder
- Biological Psychology and Neuropsychology, Institute for Psychology, University of Hamburg, Von-Melle-Park 11, 20146, Hamburg, Germany
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12
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Yuan LX, Zhao N, Wang XQ, Lv YT, He H. Echo Time Dependency of Local Activity Metrics of Resting-State Functional MRI. Front Neurosci 2021; 15:619412. [PMID: 33796007 PMCID: PMC8008056 DOI: 10.3389/fnins.2021.619412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 02/08/2021] [Indexed: 11/23/2022] Open
Abstract
Local activity metrics of resting-state functional MRI (RS-fMRI), such as the amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and degree centrality (DC), are widely used to detect brain abnormalities based on signal fluctuations. Although signal changes with echo time (TE) have been widely studied, the effect of TE on local activity metrics has not been investigated. RS-fMRI datasets from 12 healthy subjects with eyes open (EO) and eyes closed (EC) were obtained with a four-echo gradient-echo-planar imaging pulse sequence with the following parameters: repetition time/TE1/TE2/TE3/TE4 = 2,000/13/30.93/48.86/66.79 ms. Six representative regions were selected for simulating the spatial feature of TE dependency of local activity metrics. Moreover, whole-brain local activity metrics were calculated from each echo dataset and compared between EO and EC conditions. Dice overlap coefficient (DOC) was then employed to calculate the overlap between the T maps. We found that all the local activity metrics displayed different TE dependency characteristics, while their overall change patterns were similar: an initial large change followed by a slow variation. The T maps for local activity metrics also varied greatly with TE. For ALFF, fALFF, ReHo, and DC, the DOCs for voxels in four TE datasets were 6.87, 0.73, 5.08, and 0.93%, respectively. Collectively, these findings demonstrate that local metrics are greatly dependent on TE. Therefore, TE should be carefully considered for the optimization of data acquisition and multi-center data analysis in RS-fMRI.
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Affiliation(s)
- Li-Xia Yuan
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Na Zhao
- Unit of Psychiatry, Faculty of Health Sciences, Center for Cognition and Brain Sciences, Institute of Translational Medicine, University of Macau, Macao, China
| | - Xiu-Qin Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Ya-Ting Lv
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
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13
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The manifestation of individual differences in sensitivity to punishment during resting state is modulated by eye state. COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2021; 21:144-155. [PMID: 33432544 DOI: 10.3758/s13415-020-00856-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/21/2020] [Indexed: 11/08/2022]
Abstract
Structural and functional neuroimaging studies have shown that brain areas associated with fear and anxiety (defensive system areas) are modulated by individual differences in sensitivity to punishment (SP). However, little is known about how SP is related to brain functional connectivity and the factors that modulate this relationship. In this study, we investigated whether a simple methodological manipulation, such as performing a resting state with eyes open or eyes closed, can modulate the manifestation of individual differences in SP. To this end, we performed an exploratory fMRI resting state study in which a group of participants (n = 88) performed a resting state with eyes closed and another group (n = 56) performed a resting state with eyes open. All participants completed the Sensitivity to Punishment and Sensitivity to Reward Questionnaire. Seed-based functional connectivity analyses were performed in the amygdala, hippocampus, and periaqueductal gray (PAG). Our results showed that the relationship between SP and left amygdala-precuneus and left hippocampus-precuneus functional connectivity was modulated by eye state. Moreover, in the eyes open group, SP was negatively related to the functional connectivity between the PAG and amygdala and between the PAG and left hippocampus, and it was positively related to the functional connectivity between the amygdala and hippocampus. Together, our results may suggest underlying differences in the connectivity between anxiety-related areas based on eye state, which in turn would affect the manifestation of individual differences in SP.
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14
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Weng Y, Liu X, Hu H, Huang H, Zheng S, Chen Q, Song J, Cao B, Wang J, Wang S, Huang R. Open eyes and closed eyes elicit different temporal properties of brain functional networks. Neuroimage 2020; 222:117230. [PMID: 32771616 DOI: 10.1016/j.neuroimage.2020.117230] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Revised: 07/24/2020] [Accepted: 07/31/2020] [Indexed: 12/16/2022] Open
Abstract
The eyes are our windows to the brain. There are differences in brain activity between people who have their eyes closed (EC) and eyes open (EO). Previous studies focused on differences in brain functional properties between these eyes conditions based on an assumption that brain activity is a static phenomenon. However, the dynamic nature of the brain activity in different eyes conditions is still unclear. In this study, we collected resting-state fMRI data from 21 healthy subjects in the EC and EO conditions. Using a sliding time window approach and a k-means clustering algorithm, we calculated the temporal properties of dynamic functional connectivity (dFC) states in the eyes conditions. We also used graph theory to estimate the dynamic topological properties of functional networks in the two conditions. We detected two dFC states, a hyper-connected State 1 and a hypo-connected State 2. We showed the following results: (i) subjects in the EC condition stayed longer in the hyper-connected State 1 than those in the EO; (ii) subjects in the EO condition stayed longer in the hypo-connected State 2 than those in the EC; and (iii) the dFC state transformed into the other state more frequently during EC than during EO. We also found the variance of the characteristic path length was higher during EC than during EO in the hyper-connected State 1. These results indicate that brain activity may be more active and unstable during EC than during EO. Our findings may provide insights into the dynamic nature of the resting-state brain and could be a useful reference for future rs-fMRI studies.
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Affiliation(s)
- Yihe Weng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Xiaojin Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Huiqing Hu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Huiyuan Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Senning Zheng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Qinyuan Chen
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Jie Song
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Bolin Cao
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Junjing Wang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Shuai Wang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Ruiwang Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, 510631 Guangzhou, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China.
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15
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Zhou Z, Chen X, Zhang Y, Hu D, Qiao L, Yu R, Yap P, Pan G, Zhang H, Shen D. A toolbox for brain network construction and classification (BrainNetClass). Hum Brain Mapp 2020; 41:2808-2826. [PMID: 32163221 PMCID: PMC7294070 DOI: 10.1002/hbm.24979] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 02/09/2020] [Accepted: 02/25/2020] [Indexed: 12/12/2022] Open
Abstract
Brain functional network has been increasingly used in understanding brain functions and diseases. While many network construction methods have been proposed, the progress in the field still largely relies on static pairwise Pearson's correlation-based functional network and group-level comparisons. We introduce a "Brain Network Construction and Classification (BrainNetClass)" toolbox to promote more advanced brain network construction methods to the filed, including some state-of-the-art methods that were recently developed to capture complex and high-order interactions among brain regions. The toolbox also integrates a well-accepted and rigorous classification framework based on brain connectome features toward individualized disease diagnosis in a hope that the advanced network modeling could boost the subsequent classification. BrainNetClass is a MATLAB-based, open-source, cross-platform toolbox with both graphical user-friendly interfaces and a command line mode targeting cognitive neuroscientists and clinicians for promoting reliability, reproducibility, and interpretability of connectome-based, computer-aided diagnosis. It generates abundant classification-related results from network presentations to contributing features that have been largely ignored by most studies to grant users the ability of evaluating the disease diagnostic model and its robustness and generalizability. We demonstrate the effectiveness of the toolbox on real resting-state functional MRI datasets. BrainNetClass (v1.0) is available at https://github.com/zzstefan/BrainNetClass.
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Affiliation(s)
- Zhen Zhou
- College of Computer Science and TechnologyZhejiang UniversityHangzhouChina
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Xiaobo Chen
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Automotive Engineering Research InstituteJiangsu UniversityZhenjiangChina
| | - Yu Zhang
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of Psychiatry and Behavior SciencesStanford UniversityStanfordCaliforniaUSA
| | - Dan Hu
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Lishan Qiao
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- School of Mathematics ScienceLiaocheng UniversityLiaochengChina
| | - Renping Yu
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- School of Electric EngineeringZhengzhou UniversityZhengzhouChina
| | - Pew‐Thian Yap
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Gang Pan
- College of Computer Science and TechnologyZhejiang UniversityHangzhouChina
| | - Han Zhang
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Dinggang Shen
- Department of Radiology and BRICUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
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16
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Opening or closing eyes at rest modulates the functional connectivity of V1 with default and salience networks. Sci Rep 2020; 10:9137. [PMID: 32499585 PMCID: PMC7272628 DOI: 10.1038/s41598-020-66100-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 05/14/2020] [Indexed: 01/07/2023] Open
Abstract
Current evidence suggests that volitional opening or closing of the eyes modulates brain activity and connectivity. However, how the eye state influences the functional connectivity of the primary visual cortex has been poorly investigated. Using the same scanner, fMRI data from two groups of participants similar in age, sex and educational level were acquired. One group (n = 105) performed a resting state with eyes closed, and the other group (n = 63) performed a resting state with eyes open. Seed-based voxel-wise functional connectivity whole-brain analyses were performed to study differences in the connectivity of the primary visual cortex. This region showed higher connectivity with the default mode and sensorimotor networks in the eyes closed group, but higher connectivity with the salience network in the eyes open group. All these findings were replicated using an open source shared dataset. These results suggest that opening or closing the eyes may set brain functional connectivity in an interoceptive or exteroceptive state.
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17
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Zhang D, Gao Z, Liang B, Li J, Cai Y, Wang Z, Gao M, Jiao B, Huang R, Liu M. Eyes Closed Elevates Brain Intrinsic Activity of Sensory Dominance Networks: A Classifier Discrimination Analysis. Brain Connect 2019; 9:221-230. [DOI: 10.1089/brain.2018.0644] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Delong Zhang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
| | - Zhenni Gao
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Bishan Liang
- Guangdong Polytechnic Normal University, Guangzhou, China
| | - Junchao Li
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
| | - Yuxuan Cai
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
| | - Zengjian Wang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
| | - Mengxia Gao
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
| | - Bingqing Jiao
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
| | - Ruiwang Huang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
| | - Ming Liu
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China
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18
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Wei J, Chen T, Li C, Liu G, Qiu J, Wei D. Eyes-Open and Eyes-Closed Resting States With Opposite Brain Activity in Sensorimotor and Occipital Regions: Multidimensional Evidences From Machine Learning Perspective. Front Hum Neurosci 2018; 12:422. [PMID: 30405376 PMCID: PMC6200849 DOI: 10.3389/fnhum.2018.00422] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 09/28/2018] [Indexed: 01/30/2023] Open
Abstract
Studies have demonstrated that there are widespread significant differences in spontaneous brain activity between eyes-open (EO) and eyes-closed (EC) resting states. However, it remains largely unclear whether spontaneous brain activity is effectively related to EO and EC resting states. The amplitude, local functional concordance, inter-hemisphere functional synchronization, and network centrality of spontaneous brain activity were measured by the fraction amplitude of low frequency fluctuation (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC) and degree centrality (DC), respectively. Using the public Eyes-open/Eyes-closed dataset, we employed the support vector machine (SVM) and bootstrap technique to establish linking models for the fALFF, ReHo, VMHC and DC dimensions. The classification accuracies of linking models are 0.72 (0.59, 0.82), 0.88 (0.79, 0.97), 0.82 (0.74, 0.91) and 0.70 (0.62, 0.79), respectively. Specifically, we observed that brain activity in the EO condition is significantly greater in attentional system areas, including the fusiform gyrus, occipital and parietal cortex, but significantly lower in sensorimotor system areas, including the precentral/postcentral gyrus, paracentral lobule (PCL) and temporal cortex compared to the EC condition from the four dimensions. The results consistently indicated that spontaneous brain activity is effectively related to EO and EC resting states, and the two resting states are of opposite brain activity in sensorimotor and occipital regions. It may provide new insight into the neural substrate of the resting state and help computational neuroscientists or neuropsychologists to choose an appropriate resting state condition to investigate various mental disorders from the resting state functional magnetic resonance imaging (fMRI) technique.
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Affiliation(s)
- Jie Wei
- School of Electronic and Information Engineering, Southwest University, Chongqing, China.,School of Mathematics and Statistics, Southwest University, Chongqing, China.,Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, China
| | - Tong Chen
- School of Electronic and Information Engineering, Southwest University, Chongqing, China.,Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, China.,Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Chuandong Li
- School of Electronic and Information Engineering, Southwest University, Chongqing, China.,Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, China
| | - Guangyuan Liu
- School of Electronic and Information Engineering, Southwest University, Chongqing, China.,Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, China
| | - Jiang Qiu
- Department of Psychology, Southwest University, Chongqing, China
| | - Dongtao Wei
- Department of Psychology, Southwest University, Chongqing, China
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19
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Rimbert S, Al-Chwa R, Zaepffel M, Bougrain L. Electroencephalographic modulations during an open- or closed-eyes motor task. PeerJ 2018; 6:e4492. [PMID: 29576963 PMCID: PMC5857351 DOI: 10.7717/peerj.4492] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 02/20/2018] [Indexed: 01/07/2023] Open
Abstract
There is fundamental knowledge that during the resting state cerebral activity recorded by electroencephalography (EEG) is strongly modulated by the eyes-closed condition compared to the eyes-open condition, especially in the occipital lobe. However, little research has demonstrated the influence of the eyes-closed condition on the motor cortex, particularly during a self-paced movement. This prompted the question: How does the motor cortex activity change between the eyes-closed and eyes-open conditions? To answer this question, we recorded EEG signals from 15 voluntary healthy subjects who performed a simple motor task (i.e., a voluntary isometric flexion of the right-hand index) under two conditions: eyes-closed and eyes-open. Our results confirmed strong modulation in the mu rhythm (7-13 Hz) with a large event-related desynchronisation. However, no significant differences have been observed in the beta band (15-30 Hz). Furthermore, evidence suggests that the eyes-closed condition influences the behaviour of subjects. This study gives us greater insight into the motor cortex and could also be useful in the brain-computer interface (BCI) domain.
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Affiliation(s)
- Sébastien Rimbert
- Neurosys team, Inria, Villers-lès-Nancy, France
- Artificial Intelligence and Complex Systems, Université de Lorraine, LORIA, Vandœuvre-lès-Nancy, France
- Neurosys team, CNRS, LORIA, Vandœuvre-lès-Nancy, France
| | - Rahaf Al-Chwa
- Neurosys team, Inria, Villers-lès-Nancy, France
- Artificial Intelligence and Complex Systems, Université de Lorraine, LORIA, Vandœuvre-lès-Nancy, France
| | | | - Laurent Bougrain
- Neurosys team, Inria, Villers-lès-Nancy, France
- Artificial Intelligence and Complex Systems, Université de Lorraine, LORIA, Vandœuvre-lès-Nancy, France
- Neurosys team, CNRS, LORIA, Vandœuvre-lès-Nancy, France
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20
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Zhou Z, Wang JB, Zang YF, Pan G. PAIR Comparison between Two Within-Group Conditions of Resting-State fMRI Improves Classification Accuracy. Front Neurosci 2018; 11:740. [PMID: 29375288 PMCID: PMC5767225 DOI: 10.3389/fnins.2017.00740] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 12/19/2017] [Indexed: 11/13/2022] Open
Abstract
Classification approaches have been increasingly applied to differentiate patients and normal controls using resting-state functional magnetic resonance imaging data (RS-fMRI). Although most previous classification studies have reported promising accuracy within individual datasets, achieving high levels of accuracy with multiple datasets remains challenging for two main reasons: high dimensionality, and high variability across subjects. We used two independent RS-fMRI datasets (n = 31, 46, respectively) both with eyes closed (EC) and eyes open (EO) conditions. For each dataset, we first reduced the number of features to a small number of brain regions with paired t-tests, using the amplitude of low frequency fluctuation (ALFF) as a metric. Second, we employed a new method for feature extraction, named the PAIR method, examining EC and EO as paired conditions rather than independent conditions. Specifically, for each dataset, we obtained EC minus EO (EC—EO) maps of ALFF from half of subjects (n = 15 for dataset-1, n = 23 for dataset-2) and obtained EO—EC maps from the other half (n = 16 for dataset-1, n = 23 for dataset-2). A support vector machine (SVM) method was used for classification of EC RS-fMRI mapping and EO mapping. The mean classification accuracy of the PAIR method was 91.40% for dataset-1, and 92.75% for dataset-2 in the conventional frequency band of 0.01–0.08 Hz. For cross-dataset validation, we applied the classifier from dataset-1 directly to dataset-2, and vice versa. The mean accuracy of cross-dataset validation was 94.93% for dataset-1 to dataset-2 and 90.32% for dataset-2 to dataset-1 in the 0.01–0.08 Hz range. For the UNPAIR method, classification accuracy was substantially lower (mean 69.89% for dataset-1 and 82.97% for dataset-2), and was much lower for cross-dataset validation (64.69% for dataset-1 to dataset-2 and 64.98% for dataset-2 to dataset-1) in the 0.01–0.08 Hz range. In conclusion, for within-group design studies (e.g., paired conditions or follow-up studies), we recommend the PAIR method for feature extraction. In addition, dimensionality reduction with strong prior knowledge of specific brain regions should also be considered for feature selection in neuroimaging studies.
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Affiliation(s)
- Zhen Zhou
- College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Jian-Bao Wang
- Center for Cognition and Brain Disorders and the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China.,Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders and the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China.,Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China
| | - Gang Pan
- College of Computer Science and Technology, Zhejiang University, Hangzhou, China
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21
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Brodoehl S, Witte OW, Klingner CM. Measuring eye states in functional MRI. BMC Neurosci 2016; 17:48. [PMID: 27411785 PMCID: PMC4944461 DOI: 10.1186/s12868-016-0282-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 06/28/2016] [Indexed: 11/24/2022] Open
Abstract
Background In many functional magnetic resonance imaging (fMRI) studies, experimental design often depends on the eye state (i.e., whether the participants had their eyes open or closed). Closed eyes during an fMRI is the general convention, particularly when patients are in a resting-state, but the eye state is difficult to verify. Although knowledge of the impact of the eye state on brain activity is steadily growing, only a few research groups have implemented standardized procedures to monitor eye movements and eye state. These procedures involve advanced methods that are costly (e.g., fMRI-compatible cameras) and often time-consuming (e.g., EEG/EOG). Results We present a simple method that distinguishes open from closed eyes utilizing functional MR images alone. The utility of this method was demonstrated on fMRI data from 14 healthy subjects who had to open and close their eyes according to a predetermined protocol (3.0 T MRI scanner, EPI sequence with 3 × 3 × 3 mm voxels, TR 2.52 s). Conclusion The method presented herein is capable of extracting the movement direction of the eyes. All described methods are applicable for pre- and post-normalized MR images and are freely available through a MATLAB toolbox.
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Affiliation(s)
- Stefan Brodoehl
- Hans Berger Department Neurology, Jena University Hospital, Erlanger Allee 101, 07747, Jena, Germany. .,Brain Imaging Center, Jena University Hospital, Jena, Germany.
| | - Otto W Witte
- Hans Berger Department Neurology, Jena University Hospital, Erlanger Allee 101, 07747, Jena, Germany.,Brain Imaging Center, Jena University Hospital, Jena, Germany
| | - Carsten M Klingner
- Hans Berger Department Neurology, Jena University Hospital, Erlanger Allee 101, 07747, Jena, Germany.,Brain Imaging Center, Jena University Hospital, Jena, Germany
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22
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Tang C, Zhao Z, Chen C, Zheng X, Sun F, Zhang X, Tian J, Fan M, Wu Y, Jia J. Decreased Functional Connectivity of Homotopic Brain Regions in Chronic Stroke Patients: A Resting State fMRI Study. PLoS One 2016; 11:e0152875. [PMID: 27074031 PMCID: PMC4830618 DOI: 10.1371/journal.pone.0152875] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2015] [Accepted: 03/21/2016] [Indexed: 02/07/2023] Open
Abstract
The recovery of motor functions is accompanied by brain reorganization, and identifying the inter-hemispheric interaction post stroke will conduce to more targeted treatments. However, the alterations of bi-hemispheric coordination pattern between homologous areas in the whole brain for chronic stroke patients were still unclear. The present study focuses on the functional connectivity (FC) of mirror regions of the whole brain to investigate the inter-hemispheric interaction using a new fMRI method named voxel-mirrored homotopic connectivity (VMHC). Thirty left subcortical chronic stroke patients with pure motor deficits and 37 well-matched healthy controls (HCs) underwent resting-state fMRI scans. We employed a VMHC analysis to determine the brain areas showed significant differences between groups in FC between homologous regions, and we explored the relationships between the mean VMHC of each survived area and clinical tests within patient group using Pearson correlation. In addition, the brain areas showed significant correlations between the mean VMHC and clinical tests were defined as the seed regions for whole brain FC analysis. Relative to HCs, patients group displayed lower VMHC in the precentral gyrus, postcentral gyrus, inferior frontal gyrus, middle temporal gyrus, calcarine gyrus, thalamus, cerebellum anterior lobe, and cerebellum posterior lobe (CPL). Moreover, the VMHC of CPL was positively correlated with the Fugl-Meyer Score of hand (FMA-H), while a negative correlation between illness duration and the VMHC of this region was also detected. Furthermore, we found that when compared with HCs, the right CPL exhibited reduced FC with the left precentral gyrus, inferior frontal gyrus, inferior parietal lobule, middle temporal gyrus, thalamus and hippocampus. Our results suggest that the functional coordination across hemispheres is impaired in chronic stroke patients, and increased VMHC of the CPL is significantly associated with higher FMA-H scores. These findings may be helpful in understanding the mechanism of hand deficit after stroke, and the CPL may serve as a target region for hand rehabilitation following stroke.
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Affiliation(s)
- Chaozheng Tang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhiyong Zhao
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Chuang Chen
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Xiaohui Zheng
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Fenfen Sun
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Xiaoli Zhang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jing Tian
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Mingxia Fan
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Department of Rehabilitation Medicine, Jingan District Center Hospital, Shanghai, China
- * E-mail:
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23
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Feis RA, Smith SM, Filippini N, Douaud G, Dopper EGP, Heise V, Trachtenberg AJ, van Swieten JC, van Buchem MA, Rombouts SARB, Mackay CE. ICA-based artifact removal diminishes scan site differences in multi-center resting-state fMRI. Front Neurosci 2015; 9:395. [PMID: 26578859 PMCID: PMC4621866 DOI: 10.3389/fnins.2015.00395] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 10/08/2015] [Indexed: 11/17/2022] Open
Abstract
Resting-state fMRI (R-fMRI) has shown considerable promise in providing potential biomarkers for diagnosis, prognosis and drug response across a range of diseases. Incorporating R-fMRI into multi-center studies is becoming increasingly popular, imposing technical challenges on data acquisition and analysis, as fMRI data is particularly sensitive to structured noise resulting from hardware, software, and environmental differences. Here, we investigated whether a novel clean up tool for structured noise was capable of reducing center-related R-fMRI differences between healthy subjects. We analyzed three Tesla R-fMRI data from 72 subjects, half of whom were scanned with eyes closed in a Philips Achieva system in The Netherlands, and half of whom were scanned with eyes open in a Siemens Trio system in the UK. After pre-statistical processing and individual Independent Component Analysis (ICA), FMRIB's ICA-based X-noiseifier (FIX) was used to remove noise components from the data. GICA and dual regression were run and non-parametric statistics were used to compare spatial maps between groups before and after applying FIX. Large significant differences were found in all resting-state networks between study sites before using FIX, most of which were reduced to non-significant after applying FIX. The between-center difference in the medial/primary visual network, presumably reflecting a between-center difference in protocol, remained statistically significant. FIX helps facilitate multi-center R-fMRI research by diminishing structured noise from R-fMRI data. In doing so, it improves combination of existing data from different centers in new settings and comparison of rare diseases and risk genes for which adequate sample size remains a challenge.
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Affiliation(s)
- Rogier A Feis
- Department of Radiology, Leiden University Medical Centre Leiden, Netherlands ; FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK
| | - Stephen M Smith
- FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK
| | - Nicola Filippini
- FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK ; Department of Psychiatry, University of Oxford Oxford, UK
| | - Gwenaëlle Douaud
- FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK
| | - Elise G P Dopper
- Department of Radiology, Leiden University Medical Centre Leiden, Netherlands ; Department of Neurology, Erasmus Medical Centre Rotterdam, Netherlands
| | - Verena Heise
- FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK ; Department of Psychiatry, University of Oxford Oxford, UK
| | - Aaron J Trachtenberg
- FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK
| | | | - Mark A van Buchem
- Department of Radiology, Leiden University Medical Centre Leiden, Netherlands ; Leiden Institute for Brain and Cognition, Leiden University Leiden, Netherlands
| | - Serge A R B Rombouts
- Department of Radiology, Leiden University Medical Centre Leiden, Netherlands ; Leiden Institute for Brain and Cognition, Leiden University Leiden, Netherlands ; Institute of Psychology, Leiden University Leiden, Netherlands
| | - Clare E Mackay
- FMRIB, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK ; Department of Psychiatry, University of Oxford Oxford, UK
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24
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Wang XH, Li L, Xu T, Ding Z. Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchronization. PLoS One 2015; 10:e0140300. [PMID: 26469182 PMCID: PMC4607488 DOI: 10.1371/journal.pone.0140300] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Accepted: 09/23/2015] [Indexed: 01/19/2023] Open
Abstract
The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome.
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Affiliation(s)
- Xun-Heng Wang
- College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China
- * E-mail: (XHW); (LL)
| | - Lihua Li
- College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China
- * E-mail: (XHW); (LL)
| | - Tao Xu
- College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China
| | - Zhongxiang Ding
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou,310014, China
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25
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Brier MR, Mitra A, McCarthy JE, Ances BM, Snyder AZ. Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization. Neuroimage 2015. [PMID: 26208872 DOI: 10.1016/j.neuroimage.2015.07.039] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity.
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Affiliation(s)
- Matthew R Brier
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA.
| | - Anish Mitra
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - John E McCarthy
- Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
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26
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Zhang D, Liang B, Wu X, Wang Z, Xu P, Chang S, Liu B, Liu M, Huang R. Directionality of large-scale resting-state brain networks during eyes open and eyes closed conditions. Front Hum Neurosci 2015; 9:81. [PMID: 25745394 PMCID: PMC4333775 DOI: 10.3389/fnhum.2015.00081] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 02/02/2015] [Indexed: 11/13/2022] Open
Abstract
The present study examined directional connections in the brain among resting-state networks (RSNs) when the participant had their eyes open (EO) or had their eyes closed (EC). The resting-state fMRI data were collected from 20 healthy participants (9 males, 20.17 ± 2.74 years) under the EO and EC states. Independent component analysis (ICA) was applied to identify the separated RSNs (i.e., the primary/high-level visual, primary sensory-motor, ventral motor, salience/dorsal attention, and anterior/posterior default-mode networks), and the Gaussian Bayesian network (BN) learning approach was then used to explore the conditional dependencies among these RSNs. The network-to-network directional connections related to EO and EC were depicted, and a support vector machine (SVM) was further employed to identify the directional connection patterns that could effectively discriminate between the two states. The results indicated that the connections among RSNs are directionally connected within a BN during the EO and EC states. The directional connections from the salience network (SN) to the anterior/posterior default-mode networks and the high-level to primary-level visual network were the obvious characteristics of both the EO and EC resting-state BNs. Of the directional connections in BN, the directional connections of the salience and dorsal attention network (DAN) were observed to be discriminative between the EO and EC states. In particular, we noted that the properties of the salience and DANs were in opposite directions. Overall, the present study described the directional connections of RSNs using a BN learning approach during the EO and EC states, and the results suggested that the directionality of the attention systems (i.e., mainly for the salience and the DAN) in resting state might have important roles in switching between the EO and EC conditions.
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Affiliation(s)
- Delong Zhang
- Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine Guangzhou, China ; Guangzhou University of Chinese Medicine Postdoctoral Mobile Research Station Guangzhou, China
| | - Bishan Liang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University Guangzhou, China
| | - Xia Wu
- School of Information Science and Technology, Beijing Normal University Beijing, China
| | - Zengjian Wang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University Guangzhou, China
| | - Pengfei Xu
- Institute of Affective and Social Neuroscience, Shenzhen University Shenzhen, China ; Neuroimaging Center, University Medical Center Groningen, University of Groningen Groningen, Netherlands ; National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University Beijing, China
| | - Song Chang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University Guangzhou, China
| | - Bo Liu
- Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine Guangzhou, China
| | - Ming Liu
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University Guangzhou, China
| | - Ruiwang Huang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University Guangzhou, China
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