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Yi C, Chen C, Jiang L, Tao Q, Li F, Si Y, Zhang T, Yao D, Xu P. Constructing EEG Large-Scale Cortical Functional Network Connectivity Based on Brain Atlas by S Estimator. IEEE Trans Cogn Dev Syst 2021. [DOI: 10.1109/tcds.2020.2991414] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Brevers D, Cheron G, Dahman T, Petieau M, Palmero-Soler E, Foucart J, Verbanck P, Cebolla AM. Spatiotemporal brain signal associated with high and low levels of proactive motor response inhibition. Brain Res 2020; 1747:147064. [PMID: 32818530 DOI: 10.1016/j.brainres.2020.147064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 07/02/2020] [Accepted: 08/14/2020] [Indexed: 01/24/2023]
Abstract
Proactive motor response inhibition is used to strategically restrain actions in preparation for stopping. In this study, we first examined the event related potential (ERP) elicited by low and high level of proactive response inhibition, as assessed by the stop-signal task. Corroborating previous studies, we found an increased amplitude of the contingent negative variation (CNV) in the high level of proactive inhibition. As the main goal of the present study, swLORETA was used to determine the neural generators characterising CNV differences between low and high levels of proactive inhibition. Results showed that the higher level of proactive inhibition involved numerous generators, including within the middle and medial frontal gyrus. Importantly, we observed that the lower level of proactive inhibition also involved a specific neural generator, within the frontopolar cortex. Altogether, present findings identified the specific brain sources of ERP signals involved in the later phase of motor preparation under low or high levels of proactive motor response inhibition.
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Affiliation(s)
- D Brevers
- Addictive and Compulsive Behaviours Lab, Health and Behaviour Institute, University of Luxembourg, Luxembourg; Research in Psychology Applied to Motor Learning, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Psychological Medicine and Addictology, Faculty of Medicine, Brugmann-campus, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Neurophysiology and Movement Biomechanics, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium.
| | - G Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium
| | - T Dahman
- Research in Psychology Applied to Motor Learning, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium
| | - M Petieau
- Laboratory of Neurophysiology and Movement Biomechanics, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium
| | - E Palmero-Soler
- Laboratory of Neurophysiology and Movement Biomechanics, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium
| | - J Foucart
- Research in Psychology Applied to Motor Learning, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium; Haute Ecole Libre de Bruxelles (H.E.L.B.) Ilya Prigogine, Physiotherapy Section, Erasme Campus, Brussels, Belgium
| | - P Verbanck
- Research in Psychology Applied to Motor Learning, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Psychological Medicine and Addictology, Faculty of Medicine, Brugmann-campus, Université Libre de Bruxelles, Brussels, Belgium
| | - A M Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, Faculty of Motor Sciences, Erasme Campus, Université Libre de Bruxelles, Brussels, Belgium
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Ko Y, Yun SD, Hong SM, Ha Y, Choi CH, Shah NJ, Felder J. MR-compatible, 3.8 inch dual organic light-emitting diode (OLED) in-bore display for functional MRI. PLoS One 2018; 13:e0205325. [PMID: 30308026 PMCID: PMC6181352 DOI: 10.1371/journal.pone.0205325] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 09/24/2018] [Indexed: 11/19/2022] Open
Abstract
PURPOSE Functional MRI (fMRI) is a well-established method used to investigate localised brain activation by virtue of the blood oxygen level dependent (BOLD) effect. It often relies on visual presentations using beam projectors, liquid crystal display (LCD) screens, and goggle systems. In this study, we designed an MR compatible, low-cost display unit based on organic light-emitting diodes (OLED) and demonstrated its performance. METHODS A 3.8" dual OLED module and an MIPI-to-HDMI converter board were used. The OLED module was enclosed using a shielded box to prevent noise emission from the display module and the potentially destructive absorption of high power RF from the MRI transmit pulses. The front of the OLED module was covered by a conductive, transparent mesh. Power was supplied from a non-magnetic battery. The shielding of the display was evaluated by directly measuring the electromagnetic emission with the aid of a pickup loop and a low noise amplifier, as well as by examining the signal-to-noise ratio (SNR) of phantom MRI data. The visual angle of the display was calculated and compared to standard solutions. As a proof of concept of the OLED display for fMRI, a healthy volunteer was presented with a visual block paradigm. RESULTS The OLED unit was successfully installed inside a 3 T MRI scanner bore. Operation of the OLED unit did not degrade the SNR of the phantom images. The fMRI data suggest that visual stimulation can be effectively delivered to subjects with the proposed OLED unit without any significant interference between the MRI acquisitions and the display module itself. DISCUSSION We have constructed and evaluated the MR compatible, dual OLED display for fMRI studies. The proposed OLED display provides the benefits of high resolution, wide visual angle, and high contrast video images during fMRI exams.
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Affiliation(s)
- YunKyoung Ko
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
| | - Suk-Min Hong
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
| | - Yonghyun Ha
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
| | - Chang-Hoon Choi
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
- Faculty of Medicine, Department of Neurology, RWTH Aachen University, JARA, Aachen, Germany
| | - Jörg Felder
- Institute of Neuroscience and Medicine—4, Forschungszentrum Juelich, Juelich, Germany
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Yang P, Fan C, Wang M, Li L. A Comparative Study of Average, Linked Mastoid, and REST References for ERP Components Acquired during fMRI. Front Neurosci 2017; 11:247. [PMID: 28529472 PMCID: PMC5418232 DOI: 10.3389/fnins.2017.00247] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 04/18/2017] [Indexed: 12/31/2022] Open
Abstract
In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies.
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Affiliation(s)
- Ping Yang
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China
| | - Chenggui Fan
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China
| | - Min Wang
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China
| | - Ling Li
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China
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