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Bai J, Bai Y, Li X, Mu Y, Sun X, Wang B, Shang L, Di Z, Zhang W, Qiao J, Li R, Guo X, Liu X, Shi Y, Li R, Liu X. A multi-center, randomized, double-blind, sham-stimulation controlled study of transcranial magnetic stimulation with precision navigation for the treatment of multiple system atrophy. Trials 2024; 25:640. [PMID: 39350274 PMCID: PMC11440687 DOI: 10.1186/s13063-024-08458-2] [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: 11/22/2023] [Accepted: 09/05/2024] [Indexed: 10/03/2024] Open
Abstract
BACKGROUND Multiple system atrophy (MSA) is recognized as an atypical Parkinsonian syndrome, distinguished by a more rapid progression than that observed in Parkinson's disease. Unfortunately, the prognosis for MSA remains poor, with a notable absence of globally recognized effective treatments. Although preliminary studies suggest that transcranial magnetic stimulation (TMS) could potentially alleviate clinical symptoms in MSA patients, there is a significant gap in the literature regarding the optimal stimulation parameters. Furthermore, the field lacks consensus due to the paucity of robust, large-scale, multicenter trials. METHODS This investigation is a multi-center, randomized, double-blind, sham-controlled trial. We aim to enroll 96 individuals diagnosed with MSA, categorized into Parkinsonian type (MSA-P) and cerebellar type (MSA-C) according to their predominant clinical features. Participants will be randomly allocated in a 1:1 ratio to either the TMS or sham stimulation group. Utilizing advanced navigation techniques, we will ensure precise targeting for the intervention, applying theta burst stimulation (TBS). To assess the efficacy of TBS on both motor and non-motor functions, a comprehensive evaluation will be conducted using internationally recognized clinical scales and gait analysis. To objectively assess changes in brain connectivity, functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) will be employed as sensitive indicators before and after the intervention. DISCUSSION The primary aim of this study is to ascertain whether TBS can alleviate both motor and non-motor symptoms in patients with MSA. Additionally, a critical component of our research involves elucidating the underlying mechanisms through which TBS exerts its potential therapeutic effects. ETHICS AND DISSEMINATION All study protocols have been reviewed and approved by the First Affiliated Medical Ethics Committee of the Air Force Military Medical University (KY20232118-F-1). TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2300072658. Registered on 20 June 2023.
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Affiliation(s)
- Jing Bai
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Ya Bai
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Xiaobing Li
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Yaqian Mu
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Xiaolong Sun
- Department of Rehabilitation Medicine, Xijing Hospital, Xian, Shaanxi, China
| | - Bo Wang
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, Shaanxi, China
| | - Lei Shang
- Department of Health Statistics, School of Public Health, Air Force Medical University, Xi'an, Shaanxi, China
| | - Zhengli Di
- Department of Neurology, Xi'an Central Hospital, Xi'an, Shaanxi, China
| | - Wei Zhang
- Department of Neurology, Tangdu Hospital, Xi'an, Shaanxi, China
| | - Jin Qiao
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Rui Li
- Department of Neurology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Xin Guo
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Xinyao Liu
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Yan Shi
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Rui Li
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China
| | - Xuedong Liu
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xian, Shaanxi, China.
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Zhang Z, Huang Y, Chen X, Li J, Yang Y, Lv L, Wang J, Wang M, Wang Y, Wang Z. State-specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2402718. [PMID: 38938001 PMCID: PMC11434125 DOI: 10.1002/advs.202402718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 06/03/2024] [Indexed: 06/29/2024]
Abstract
Long-range thalamocortical communication is central to anesthesia-induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state-specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram-fuctional magnetic resonance imaging (EEG-fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely-tuned propofol anesthesia. This approach led to the identification of an intralaminar-driven network responsible for rapid arousal during slow-wave oscillations. A network-based RNA-sequencing analysis is conducted of region-, layer-, and cell-specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin-expressing neurons, and oligodendrocytes. Comparison with human RNA-sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network-focused transcriptional signatures of arousal.
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Affiliation(s)
- Zhao Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, 12 Urumqi Middle Rd, Jing'an District, Shanghai, 200040, China
| | - Yichun Huang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
| | - Xiaoyu Chen
- Institute of Natural Sciences and School of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan RD, Minhang District, Shanghai, 200240, China
| | - Jiahui Li
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
| | - Yi Yang
- Department of Neurosurgery, Brain Computer Interface Transition Research Center, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring Rd West, Fengtai District, Beijing, 100070, China
| | - Longbao Lv
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, 32 East of Jiaochang Rd, Kunming, Yunnan, 650223, China
| | - Jianhong Wang
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, 32 East of Jiaochang Rd, Kunming, Yunnan, 650223, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, 450003, China
| | - Yingwei Wang
- Department of Anesthesiology, Huashan Hospital, Fudan University, 12 Urumqi Middle Rd, Jing'an District, Shanghai, 200040, China
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
- School of Biomedical Engineering, Hainan University, 58 Renmin Avenue, Haikou, Hainan, 570228, China
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Amador-Tejada A, McGillivray JE, Kumbhare DA, Noseworthy MD. Denoising of the gradient artifact present in simultaneous studies of muscle blood oxygen level dependent (BOLD) signal and electromyography (EMG). Magn Reson Imaging 2024; 111:179-185. [PMID: 38723782 DOI: 10.1016/j.mri.2024.05.004] [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: 03/12/2024] [Revised: 04/28/2024] [Accepted: 05/06/2024] [Indexed: 05/19/2024]
Abstract
The MR-induced gradient artifact affects EMG recordings during simultaneous muscle BOLD/EMG acquisitions. However, no dedicated hardware can remove the gradient artifact easily, and alternative methods are expensive and time-consuming. This study aimed to develop three denoising methods requiring different processing levels and MR-compatible hardware. At two time points, surface EMG was recorded from the lower leg of 6 participants (50:50 sex ratio, age = 26.24.6 yrs., height = 173.59.2 cm, weight = 71.511.4 kg) using a plantar flexion-based block design consisting of 30s of rest followed by 30s of flexion for 5 min, under three conditions: inside the MRI bore, with and without a BOLD sequence (3 T, BOLD sequence, GRE EPI, 10 slices, 64×64 matrix, 2 mm thickness, and TE/TR/flip = 35/3000 ms/70), and outside the MRI environment. Simultaneous BOLD/EMG recordings were denoised using average artifact subtraction with three methods of artifact template creation, each having varying timing and hardware requirements. Method M1 builds the artifact template by recording the scanner triggers coming from the MRI; M2 creates the artifact template with a constant artifact period computed as TR/[number of slices]; M3 estimates the artifact template by looking at the periodicity of the gradient artifact located in the EMG recordings. Following postprocessing, SNR analysis was performed, comparing rest-to-flexion periods, to assess the efficacy of denoising methods and to compare differences between conditions. Linear mixed-effects models showed no significant differences in the mean SNR between denoising methods (p = 0.656). Furthermore, EMG SNR measurements were significantly affected by the magnetic environment (p < 0.05) but not by muscle fatigue over time (p = 0.975). EMG recordings contaminated with gradient artifacts during simultaneous BOLD/EMG can be efficiently denoised using all proposed methods, with two methods requiring no extra hardware. With minimal post-processing, EMG can easily be performed during muscle BOLD MRI studies.
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Affiliation(s)
- Alejandro Amador-Tejada
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada; Imaging Research Centre, St. Joseph's Healthcare, Hamilton, ON, Canada
| | - Joshua E McGillivray
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada; Imaging Research Centre, St. Joseph's Healthcare, Hamilton, ON, Canada
| | - Dinesh A Kumbhare
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada; Department of Medicine, Division of Physical Medicine and Rehabilitation, University of Toronto, Toronto, ON, Canada
| | - Michael D Noseworthy
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada; Imaging Research Centre, St. Joseph's Healthcare, Hamilton, ON, Canada; Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada; Department of Radiology, McMaster University, Hamilton, ON, Canada.
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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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5
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Verdonk C, Teed AR, White EJ, Ren X, Stewart JL, Paulus MP, Khalsa SS. Heartbeat-evoked neural response abnormalities in generalized anxiety disorder during peripheral adrenergic stimulation. Neuropsychopharmacology 2024; 49:1246-1254. [PMID: 38291167 PMCID: PMC11224228 DOI: 10.1038/s41386-024-01806-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 12/22/2023] [Accepted: 01/16/2024] [Indexed: 02/01/2024]
Abstract
Hyperarousal symptoms in generalized anxiety disorder (GAD) are often incongruent with the observed physiological state, suggesting that abnormal processing of interoceptive signals is a characteristic feature of the disorder. To examine the neural mechanisms underlying interoceptive dysfunction in GAD, we evaluated whether adrenergic modulation of cardiovascular signaling differentially affects the heartbeat-evoked potential (HEP), an electrophysiological marker of cardiac interoception, during concurrent electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) scanning. Intravenous infusions of the peripheral adrenergic agonist isoproterenol (0.5 and 2.0 micrograms, μg) were administered in a randomized, double-blinded and placebo-controlled fashion to dynamically perturb the cardiovascular system while recording the associated EEG-fMRI responses. During the 0.5 μg isoproterenol infusion, the GAD group (n = 24) exhibited significantly larger changes in HEP amplitude in an opposite direction than the healthy comparison (HC) group (n = 24). In addition, the GAD group showed significantly larger absolute HEP amplitudes than the HC group during saline infusions, when cardiovascular tone did not increase. No significant group differences in HEP amplitude were identified during the 2.0 μg isoproterenol infusion. Using analyzable blood oxygenation level-dependent fMRI data from participants with concurrent EEG-fMRI data (21 GAD and 21 HC), we found that the aforementioned HEP effects were uncorrelated with fMRI signals in the insula, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, amygdala, and somatosensory cortex, brain regions implicated in cardiac signal processing in prior fMRI studies. These findings provide additional evidence of dysfunctional cardiac interoception in GAD and identify neural processes at the electrophysiological level that may be independent from blood oxygen level-dependent responses during peripheral adrenergic stimulation.
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Affiliation(s)
- Charles Verdonk
- Laureate Institute for Brain Research, Tulsa, OK, USA
- VIFASOM (EA 7330 Vigilance Fatigue, Sommeil et Santé Publique), Université Paris Cité, Paris, France
- French Armed Forces Biomedical Research Institute, Brétigny-sur-Orge, France
| | - Adam R Teed
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Evan J White
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Xi Ren
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Jennifer L Stewart
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, USA
| | - Martin P Paulus
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, USA
| | - Sahib S Khalsa
- Laureate Institute for Brain Research, Tulsa, OK, USA.
- Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, USA.
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6
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Pei H, Jiang S, Liu M, Ye G, Qin Y, Liu Y, Duan M, Yao D, Luo C. Simultaneous EEG-fMRI Investigation of Rhythm-Dependent Thalamo-Cortical Circuits Alteration in Schizophrenia. Int J Neural Syst 2024; 34:2450031. [PMID: 38623649 DOI: 10.1142/s012906572450031x] [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] [Indexed: 04/17/2024]
Abstract
Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.
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Affiliation(s)
- Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mei Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Guofeng Ye
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yun Qin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yayun Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mingjun Duan
- Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation Chinese, Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation Chinese, Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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Wirsich J, Iannotti GR, Ridley B, Shamshiri EA, Sheybani L, Grouiller F, Bartolomei F, Seeck M, Lazeyras F, Ranjeva JP, Guye M, Vulliemoz S. Altered correlation of concurrently recorded EEG-fMRI connectomes in temporal lobe epilepsy. Netw Neurosci 2024; 8:466-485. [PMID: 38952816 PMCID: PMC11142634 DOI: 10.1162/netn_a_00362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 01/17/2024] [Indexed: 07/03/2024] Open
Abstract
Whole-brain functional connectivity networks (connectomes) have been characterized at different scales in humans using EEG and fMRI. Multimodal epileptic networks have also been investigated, but the relationship between EEG and fMRI defined networks on a whole-brain scale is unclear. A unified multimodal connectome description, mapping healthy and pathological networks would close this knowledge gap. Here, we characterize the spatial correlation between the EEG and fMRI connectomes in right and left temporal lobe epilepsy (rTLE/lTLE). From two centers, we acquired resting-state concurrent EEG-fMRI of 35 healthy controls and 34 TLE patients. EEG-fMRI data was projected into the Desikan brain atlas, and functional connectomes from both modalities were correlated. EEG and fMRI connectomes were moderately correlated. This correlation was increased in rTLE when compared to controls for EEG-delta/theta/alpha/beta. Conversely, multimodal correlation in lTLE was decreased in respect to controls for EEG-beta. While the alteration was global in rTLE, in lTLE it was locally linked to the default mode network. The increased multimodal correlation in rTLE and decreased correlation in lTLE suggests a modality-specific lateralized differential reorganization in TLE, which needs to be considered when comparing results from different modalities. Each modality provides distinct information, highlighting the benefit of multimodal assessment in epilepsy.
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Affiliation(s)
- Jonathan Wirsich
- EEG and Epilepsy Unit, Division of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Giannina Rita Iannotti
- EEG and Epilepsy Unit, Division of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Ben Ridley
- Aix-Marseille Univ, CNRS, CRMBM 7339, Marseille, France
- AP-HM CHU Timone, CEMEREM, Marseille, France
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Elhum A. Shamshiri
- EEG and Epilepsy Unit, Division of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Laurent Sheybani
- EEG and Epilepsy Unit, Division of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
- UCL Queen Square Institute of Neurology, Queen Square, London, UK
| | - Frédéric Grouiller
- Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Fabrice Bartolomei
- Aix-Marseille Univ, INS, INSERM, UMR 1106, Marseille, France
- AP-HM CHU Timone, Service d’épileptologie, Marseille, France
| | - Margitta Seeck
- EEG and Epilepsy Unit, Division of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - François Lazeyras
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Jean-Philippe Ranjeva
- Aix-Marseille Univ, CNRS, CRMBM 7339, Marseille, France
- AP-HM CHU Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix-Marseille Univ, CNRS, CRMBM 7339, Marseille, France
- AP-HM CHU Timone, CEMEREM, Marseille, France
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Division of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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Dabbagh A, Horn U, Kaptan M, Mildner T, Müller R, Lepsien J, Weiskopf N, Brooks JCW, Finsterbusch J, Eippert F. Reliability of task-based fMRI in the dorsal horn of the human spinal cord. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.22.572825. [PMID: 38187724 PMCID: PMC10769329 DOI: 10.1101/2023.12.22.572825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across two consecutive days in 40 healthy volunteers. We assessed the test-retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat pain stimuli (1s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both β-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with fair reliability across days. Taken together, these results demonstrate that heat pain stimuli as short as one second are able to evoke a robust and spatially specific BOLD response, which is however strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.
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Affiliation(s)
- Alice Dabbagh
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ulrike Horn
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Merve Kaptan
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, CA, USA
| | - Toralf Mildner
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roland Müller
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jöran Lepsien
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
| | - Jonathan C W Brooks
- School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), Norwich, United Kingdom
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Iwama S, Tsuchimoto S, Mizuguchi N, Ushiba J. EEG decoding with spatiotemporal convolutional neural network for visualization and closed-loop control of sensorimotor activities: A simultaneous EEG-fMRI study. Hum Brain Mapp 2024; 45:e26767. [PMID: 38923184 PMCID: PMC11199199 DOI: 10.1002/hbm.26767] [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: 01/08/2024] [Revised: 06/06/2024] [Accepted: 06/10/2024] [Indexed: 06/28/2024] Open
Abstract
Closed-loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the associated behavioral performance. A spatiotemporal filter for high-density whole-head scalp EEG using a convolutional neural network can overcome the ambiguity of the signaling source because each EEG signal includes information on the remote regions. We simultaneously acquired EEG and functional magnetic resonance images in humans during the brain-computer interface (BCI) based neurofeedback training and compared the reconstructed and modeled hemodynamic responses of the sensorimotor network. Filters constructed with a convolutional neural network captured activities in the targeted network with spatial precision and specificity superior to those of the EEG signals preprocessed with standard pipelines used in BCI-based neurofeedback paradigms. The middle layers of the trained model were examined to characterize the neuronal oscillatory features that contributed to the reconstruction. Analysis of the layers for spatial convolution revealed the contribution of distributed cortical circuitries to reconstruction, including the frontoparietal and sensorimotor areas, and those of temporal convolution layers that successfully reconstructed the hemodynamic response function. Employing a spatiotemporal filter and leveraging the electrophysiological signatures of the sensorimotor excitability identified in our middle layer analysis would contribute to the development of a further effective neurofeedback intervention.
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Affiliation(s)
- Seitaro Iwama
- Department of Biosciences and Informatics, Faculty of Science and TechnologyKeio UniversityYokohamaJapan
| | - Shohei Tsuchimoto
- School of Fundamental Science and TechnologyGraduate School of Keio UniversityYokohamaJapan
- Department of System NeuroscienceNational Institute for Physiological SciencesOkazakiJapan
| | - Nobuaki Mizuguchi
- Research Organization of Science and TechnologyRitsumeikan UniversityKusatsuJapan
- Institute of Advanced Research for Sport and Health ScienceRitsumeikan UniversityKusatsuJapan
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and TechnologyKeio UniversityYokohamaJapan
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10
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Ghouse A, Pfurtscheller G, Schwarz G, Valenza G. Uncovering Hemispheric Asymmetry and Directed Oscillatory Brain-Heart Interplay in Anxiety Processing: An fMRI Study. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1984-1993. [PMID: 38748531 DOI: 10.1109/tnsre.2024.3401577] [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: 05/25/2024]
Abstract
Brain-heart interactions (BHI) are critical for generating and processing emotions, including anxiety. Understanding specific neural correlates would be instrumental for greater comprehension and potential therapeutic interventions of anxiety disorders. While prior work has implicated the pontine structure as a central processor in cardiac regulation in anxiety, the distributed nature of anxiety processing across the cortex remains elusive. To address this, we performed a whole-brain-heart analysis using the full frequency directed transfer function to study resting-state spectral differences in BHI between high and low anxiety groups undergoing fMRI scans. Our findings revealed a hemispheric asymmetry in low-frequency interplay (0.05 Hz - 0.15 Hz) characterized by ascending BHI to the left insula and descending BHI from the right insula. Furthermore, we provide evidence supporting the "pacemaker hypothesis", highlighting the pons' function in regulating cardiac activity. Higher frequency interplay (0.2 Hz - 0.4Hz) demonstrate a preference for ascending interactions, particularly towards ventral prefrontal cortical activity in high anxiety groups, suggesting the heart's role in triggering a cognitive response to regulate anxiety. These findings highlight the impact of anxiety on BHI, contributing to a better understanding of its effect on the resting-state fMRI signal, with further implications for potential therapeutic interventions in treating anxiety disorders.
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11
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Jiang S, Pei H, Chen J, Li H, Liu Z, Wang Y, Gong J, Wang S, Li Q, Duan M, Calhoun VD, Yao D, Luo C. Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges. Int J Neural Syst 2024; 34:2450017. [PMID: 38372049 DOI: 10.1142/s0129065724500175] [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] [Indexed: 02/20/2024]
Abstract
Idiopathic generalized epilepsy (IGE) is characterized by cryptogenic etiology and the striatum and cerebellum are recognized as modulators of epileptic network. We collected simultaneous electroencephalogram and functional magnetic resonance imaging data from 145 patients with IGE, 34 of whom recorded interictal epileptic discharges (IEDs) during scanning. In states without IEDs, hierarchical connectivity was performed to search core cortical regions which might be potentially modulated by striatum and cerebellum. Node-node and edge-edge moderation models were constructed to depict direct and indirect moderation effects in states with and without IEDs. Patients showed increased hierarchical connectivity with sensorimotor cortices (SMC) and decreased connectivity with regions in the default mode network (DMN). In the state without IEDs, striatum, cerebellum, and thalamus were linked to weaken the interactions of regions in the salience network (SN) with DMN and SMC. In periods with IEDs, overall increased moderation effects on the interaction between regions in SN and DMN, and between regions in DMN and SMC were observed. The thalamus and striatum were implicated in weakening interactions between regions in SN and SMC. The striatum and cerebellum moderated the cortical interaction among DMN, SN, and SMC in alliance with the thalamus, contributing to the dysfunction in states with and without IEDs in IGE. The current work revealed state-specific modulation effects of striatum and cerebellum on thalamocortical circuits and uncovered the potential core cortical targets which might contribute to develop new clinical neuromodulation techniques.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Junxia Chen
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Zetao Liu
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Yuehan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Jinnan Gong
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- School of Computer Science, Chengdu University of Information Technology, Chengdu, P. R. China
| | - Sheng Wang
- Department of Neurology, Hainan Medical University, Hainan 571199, P. R. China
| | - Qifu Li
- Department of Neurology, Hainan Medical University, Hainan 571199, P. R. China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, P. R. China
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
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12
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Dien J. Multi-Algorithm Artifact Correction (MAAC) procedure part one: Algorithm and example. Biol Psychol 2024; 188:108775. [PMID: 38499226 DOI: 10.1016/j.biopsycho.2024.108775] [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: 03/01/2021] [Revised: 03/10/2024] [Accepted: 03/14/2024] [Indexed: 03/20/2024]
Abstract
The Multi-Algorithm Artifact Correction (MAAC) procedure is presented for electroencephalographic (EEG) data, as made freely available in the open-source EP Toolkit (Dien, 2010). First the major EEG artifact correction methods (regression, spatial filters, principal components analysis, and independent components analysis) are reviewed. Contrary to the dominant approach of picking one method that is thought to be most effective, this review concludes that none are globally superior, but rather each has strengths and weaknesses. Then each of the major artifact types are reviewed (Blink, Corneo-Retinal Dipole, Saccadic Spike Potential, and Movement). For each one, it is proposed that one of the major correction methods is best matched to address it, resulting in the MAAC procedure. The MAAC itself is then presented, as implemented in the EP Toolkit, in order to provide a sense of the user experience. The primary goal of this present paper is to make the conceptual argument for the MAAC approach.
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Affiliation(s)
- Joseph Dien
- Department of Human Development and Quantitative Methodology, University of Maryland, 3304 Benjamin Building, College Park, MD 20742, USA.
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13
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Medeiros J, Simões M, Castelhano J, Abreu R, Couceiro R, Henriques J, Castelo-Branco M, Madeira H, Teixeira C, de Carvalho P. EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study. PLoS One 2024; 19:e0299108. [PMID: 38452019 PMCID: PMC10919648 DOI: 10.1371/journal.pone.0299108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 02/06/2024] [Indexed: 03/09/2024] Open
Abstract
Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.
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Affiliation(s)
- Júlio Medeiros
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Marco Simões
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - João Castelhano
- ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Rodolfo Abreu
- ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Ricardo Couceiro
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Jorge Henriques
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Henrique Madeira
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - César Teixeira
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Paulo de Carvalho
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
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14
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Fang F, Teixeira AL, Li R, Zou L, Zhang Y. The control patterns of affective processing and cognitive reappraisal: insights from brain controllability analysis. Cereb Cortex 2024; 34:bhad500. [PMID: 38216523 DOI: 10.1093/cercor/bhad500] [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: 10/10/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 01/14/2024] Open
Abstract
Perceiving and modulating emotions is vital for cognitive function and is often impaired in neuropsychiatric conditions. Current tools for evaluating emotional dysregulation suffer from subjectivity and lack of precision, especially when it comes to understanding emotion from a regulatory or control-based perspective. To address these limitations, this study leverages an advanced methodology known as functional brain controllability analysis. We simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data from 17 healthy subjects engaged in emotion processing and regulation tasks. We then employed a novel EEG/fMRI integration technique to reconstruct cortical activity in a high spatiotemporal resolution manner. Subsequently, we conducted functional brain controllability analysis to explore the neural network control patterns underlying different emotion conditions. Our findings demonstrated that the dorsolateral and ventrolateral prefrontal cortex exhibited increased controllability during the processing and regulation of negative emotions compared to processing of neutral emotion. Besides, the anterior cingulate cortex was notably more active in managing negative emotion than in either controlling neutral emotion or regulating negative emotion. Finally, the posterior parietal cortex emerged as a central network controller for the regulation of negative emotion. This study offers valuable insights into the cortical control mechanisms that support emotion perception and regulation.
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Affiliation(s)
- Feng Fang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Antonio L Teixeira
- Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Rihui Li
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, China
| | - Ling Zou
- School of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu, China
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
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15
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Zhang Y, Wu X, Sun J, Yue K, Lu S, Wang B, Liu W, Shi H, Zou L. Exploring changes in brain function in IBD patients using SPCCA: a study of simultaneous EEG-fMRI. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2024; 21:2646-2670. [PMID: 38454700 DOI: 10.3934/mbe.2024117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2024]
Abstract
Research on functional changes in the brain of inflammatory bowel disease (IBD) patients is emerging around the world, which brings new perspectives to medical research. In this paper, the methods of canonical correlation analysis (CCA), kernel canonical correlation analysis (KCCA), and sparsity preserving canonical correlation analysis (SPCCA) were applied to the fusion of simultaneous EEG-fMRI data from 25 IBD patients and 15 healthy individuals. The CCA, KCCA and SPCCA fusion methods were used for data processing to compare the results obtained by the three methods. The results clearly show that there is a significant difference in the activation intensity between IBD and healthy control (HC), not only in the frontal lobe (p < 0.01) and temporal lobe (p < 0.01) regions, but also in the posterior cingulate gyrus (p < 0.01), gyrus rectus (p < 0.01), and amygdala (p < 0.01) regions, which are usually neglected. The mean difference in the SPCCA activation intensity was 60.1. However, the mean difference in activation intensity was only 36.9 and 49.8 by using CCA and KCCA. In addition, the correlation of the relevant components selected during the SPCCA calculation was high, with correlation components of up to 0.955; alternatively, the correlations obtained from CCA and KCCA calculations were only 0.917 and 0.926, respectively. It can be seen that SPCCA is indeed superior to CCA and KCCA in processing high-dimensional multimodal data. This work reveals the process of analyzing the brain activation state in IBD disease, provides a further perspective for the study of brain function, and opens up a new avenue for studying the SPCCA method and the change in the intensity of brain activation in IBD disease.
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Affiliation(s)
- Yin Zhang
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Xintong Wu
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Jingwen Sun
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Kecen Yue
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Shuangshuang Lu
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Bingjian Wang
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Wenjia Liu
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Haifeng Shi
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Department of Radiology, China
| | - Ling Zou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
- School of Computer and Artificial Intelligence, Changzhou University, Changzhou, Jiangsu 213164, China
- Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou 310018, China
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16
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Boutin A, Gabitov E, Pinsard B, Boré A, Carrier J, Doyon J. Temporal cluster-based organization of sleep spindles underlies motor memory consolidation. Proc Biol Sci 2024; 291:20231408. [PMID: 38196349 PMCID: PMC10777148 DOI: 10.1098/rspb.2023.1408] [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: 06/28/2023] [Accepted: 12/04/2023] [Indexed: 01/11/2024] Open
Abstract
Sleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remain unclear. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organized patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only. Altogether, our findings suggest that spindles' clustering and rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronized oscillatory activity within a subcortical-cortical network involved during learning.
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Affiliation(s)
- Arnaud Boutin
- CIAMS, Université Paris-Saclay, 91405 Orsay, France
- CIAMS, Université d'Orléans, 45067 Orléans, France
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada H3A 2B4
- Functional Neuroimaging Unit, C.R.I.U.G.M, Montréal, QC, Canada H3W 1W5
- Department of Psychology, Université de Montréal, Montréal, QC, Canada H3T 1J4
| | - Ella Gabitov
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada H3A 2B4
- Functional Neuroimaging Unit, C.R.I.U.G.M, Montréal, QC, Canada H3W 1W5
- Department of Psychology, Université de Montréal, Montréal, QC, Canada H3T 1J4
| | - Basile Pinsard
- Functional Neuroimaging Unit, C.R.I.U.G.M, Montréal, QC, Canada H3W 1W5
- Department of Psychology, Université de Montréal, Montréal, QC, Canada H3T 1J4
| | - Arnaud Boré
- Functional Neuroimaging Unit, C.R.I.U.G.M, Montréal, QC, Canada H3W 1W5
| | - Julie Carrier
- Functional Neuroimaging Unit, C.R.I.U.G.M, Montréal, QC, Canada H3W 1W5
- Department of Psychology, Université de Montréal, Montréal, QC, Canada H3T 1J4
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montréal, QC, Canada H4J 1C5
| | - Julien Doyon
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada H3A 2B4
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada H3A 2B4
- Functional Neuroimaging Unit, C.R.I.U.G.M, Montréal, QC, Canada H3W 1W5
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Bergamo D, Handjaras G, Petruso F, Talami F, Ricciardi E, Benuzzi F, Vaudano AE, Meletti S, Bernardi G, Betta M. Maturation-dependent changes in cortical and thalamic activity during sleep slow waves: Insights from a combined EEG-fMRI study. Sleep Med 2024; 113:357-369. [PMID: 38113618 DOI: 10.1016/j.sleep.2023.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/24/2023] [Accepted: 12/02/2023] [Indexed: 12/21/2023]
Abstract
INTRODUCTION Studies using scalp EEG have shown that slow waves (0.5-4 Hz), the most prominent hallmark of NREM sleep, undergo relevant changes from childhood to adulthood, mirroring brain structural modifications and the acquisition of cognitive skills. Here we used simultaneous EEG-fMRI to investigate the cortical and subcortical correlates of slow waves in school-age children and determine their relative developmental changes. METHODS We analyzed data from 14 school-age children with self-limited focal epilepsy of childhood who fell asleep during EEG-fMRI recordings. Brain regions associated with slow-wave occurrence were identified using a voxel-wise regression that also modelled interictal epileptic discharges and sleep spindles. At the group level, a mixed-effects linear model was used. The results were qualitatively compared with those obtained from 2 adolescents with epilepsy and 17 healthy adults. RESULTS Slow waves were associated with hemodynamic-signal decreases in bilateral somatomotor areas. Such changes extended more posteriorly relative to those in adults. Moreover, the involvement of areas belonging to the default mode network changes as a function of age. No significant hemodynamic responses were observed in subcortical structures. However, we identified a significant correlation between age and thalamic hemodynamic changes. CONCLUSIONS Present findings indicate that the somatomotor cortex may have a key role in slow-wave expression throughout the lifespan. At the same time, they are consistent with a posterior-to-anterior shift in slow-wave distribution mirroring brain maturational changes. Finally, our results suggest that slow-wave changes may not reflect only neocortical modifications but also the maturation of subcortical structures, including the thalamus.
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Affiliation(s)
- Damiana Bergamo
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | | | - Flavia Petruso
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy; Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Francesca Talami
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | | | - Francesca Benuzzi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | - Giulio Bernardi
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Monica Betta
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.
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18
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Verdonk C, Teed AR, White EJ, Ren X, Stewart JL, Paulus MP, Khalsa SS. Heartbeat-evoked neural response abnormalities in generalized anxiety disorder during peripheral adrenergic stimulation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.09.23291166. [PMID: 37398268 PMCID: PMC10312828 DOI: 10.1101/2023.06.09.23291166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Hyperarousal symptoms in generalized anxiety disorder (GAD) are often incongruent with the observed physiological state, suggesting that abnormal processing of interoceptive signals is a characteristic feature of the disorder. To examine the neural mechanisms underlying interoceptive dysfunction in GAD, we evaluated whether adrenergic modulation of cardiovascular signaling differentially affects the heartbeat evoked potential (HEP), an electrophysiological marker of cardiac interoception, during concurrent electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) scanning. Intravenous infusions of the peripheral adrenergic agonist isoproterenol (0.5 and 2.0 micrograms, μg) were administered in a randomized, double-blinded and placebo-controlled fashion to dynamically perturb the cardiovascular system while recording the associated EEG-fMRI responses. During the 0.5 μg isoproterenol infusion, the GAD group (n=24) exhibited significantly larger changes in HEP amplitude in an opposite direction than the HC group (n=24). In addition, the GAD group showed significantly larger absolute HEP amplitudes than HC during saline infusions, when cardiovascular tone did not increase. No significant group differences in HEP amplitude were identified during the 2.0 μg isoproterenol infusion. Using analyzable blood oxygenation level dependent fMRI data from participants with concurrent EEG-fMRI data (21 GAD and 21 HC), we found that the aforementioned HEP effects were uncorrelated with fMRI signals in the insula, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, amygdala, and somatosensory cortex, brain regions implicated in cardiac signal processing according to prior fMRI studies. These findings provide additional evidence of dysfunctional cardiac interoception in GAD and identify neural processes at the electrophysiological level that may be independent from blood oxygen level-dependent responses during peripheral adrenergic stimulation.
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Affiliation(s)
- Charles Verdonk
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
- VIFASOM (EA 7330 Vigilance Fatigue, Sommeil et Santé Publique), Université Paris Cité, Paris, France
- French Armed Forces Biomedical Research Institute, Brétigny-sur-Orge, France
| | - Adam R. Teed
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
| | - Evan J. White
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
| | - Xi Ren
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
| | - Jennifer L. Stewart
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
- Oxley College of Health Sciences, University of Tulsa, Tulsa, Oklahoma, United States
| | - Martin P. Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
- Oxley College of Health Sciences, University of Tulsa, Tulsa, Oklahoma, United States
| | - Sahib S. Khalsa
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States
- Oxley College of Health Sciences, University of Tulsa, Tulsa, Oklahoma, United States
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Miletínová E, Piorecký M, Koudelka V, Jiříček S, Tomeček D, Brunovský M, Horáček J, Bušková J. Alterations of sleep initiation in NREM parasomnia after sleep deprivation - A multimodal pilot study. Sleep Med X 2023; 6:100086. [PMID: 37745863 PMCID: PMC10511487 DOI: 10.1016/j.sleepx.2023.100086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/24/2023] [Accepted: 09/11/2023] [Indexed: 09/26/2023] Open
Abstract
Objectives NREM parasomnias also known as disorders of arousal (DOA) are characterised by abnormal motor and autonomic activation during arousals primarily from slow wave sleep. Dissociative state between sleep and wake is likely responsible for clinical symptoms of DOA. We therefore investigated potential dissociation outside of parasomnic events by using simultaneous 256-channel EEG (hdEEG) and functional magnetic resonance imaging (fMRI). Methods Eight DOA patients (3 women, mean age = 27.8; SD = 4.2) and 8 gender and age matched healthy volunteers (3 women, mean age = 26,5; SD = 4.0) were included into the study. They underwent 30-32 h of sleep deprivation followed by hdEEG and fMRI recording. We determined 2 conditions: falling asleep (FA) and arousal (A), that occurred outside of deep sleep and/or parasomnic event. We used multimodal approach using data obtained from EEG, fMRI and EEG-fMRI integration approach. Results DOA patients showed increase in delta and beta activity over postcentral gyrus and cuneus during awakening period. This group expressed increased connectivity between motor cortex and cingulate during arousals unrelated to parasomnic events in the beta frequency band. They also showed lower connectivity between different portions of cingulum. In contrast, the greater connectivity was found between thalamus and some cortical areas, such as occipital cortex. Conclusion Our findings suggest a complex alteration in falling asleep and arousal mechanisms at both subcortical and cortical levels in response to sleep deprivation. As this alteration is present also outside of slow wave sleep and/or parasomnic episodes we believe this could be a trait factor of DOA.
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Affiliation(s)
- E. Miletínová
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
| | - M. Piorecký
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Department of Biomedical Technology, Faculty of Biomedical Engineering, CTU in Prague, Czech Republic
| | - V. Koudelka
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Department of Biomedical Technology, Faculty of Biomedical Engineering, CTU in Prague, Czech Republic
| | - S. Jiříček
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - D. Tomeček
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - M. Brunovský
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
| | - J. Horáček
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
| | - J. Bušková
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
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20
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Nuttall R, El Mir A, Jäger C, Letz S, Wohlschläger A, Schneider G. Broadly applicable methods for the detection of artefacts in electroencephalography acquired simultaneously with hemodynamic recordings. MethodsX 2023; 11:102376. [PMID: 37767154 PMCID: PMC10520509 DOI: 10.1016/j.mex.2023.102376] [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: 07/31/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Electroencephalography (EEG) data, acquired simultaneously with magnetic resonance imaging (MRI), must be corrected for artefacts related to MR gradient switches (GS) and the cardioballistic (CB) effect. Canonical approaches require additional signal acquisition for artefact detection (e.g., MR volume onsets, ECG), without which the EEG data would be rendered uncleanable from these artefacts.•We present two broadly applicable methods for artefact detection based on peak detection combined with temporal constraints with respect to periodicity directly from the EEG data itself; no additional signals are required. We validated the performance of our methods versus the two canonical approaches for detection of GS/CB artefact, respectively, on 26 healthy human EEG-functional MRI resting-state datasets. Utilising various performance metrics, we found our methods to perform as well as - and sometimes better than - the canonical standard approaches. With as little as one EEG channel recording, our methods can be applied to detect GS/CB artefacts in EEG data acquired simultaneously with MRI in the absence of MR volume onsets and/or an ECG recording. The detected artefact onsets can then be fed into the standard artefact correction software.
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Affiliation(s)
- Rachel Nuttall
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich 81675, Germany
| | - Aya El Mir
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich 81675, Germany
- New York University Abu Dhabi, Engineering Division, Saadiyat Marina District, Abu Dhabi, United Arab Emirates
| | - Cilia Jäger
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich 81675, Germany
| | - Svenja Letz
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich 81675, Germany
| | - Afra Wohlschläger
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich 81675, Germany
| | - Gerhard Schneider
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich 81675, Germany
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21
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Caetano G, Esteves I, Vourvopoulos A, Fleury M, Figueiredo P. NeuXus open-source tool for real-time artifact reduction in simultaneous EEG-fMRI. Neuroimage 2023; 280:120353. [PMID: 37652114 DOI: 10.1016/j.neuroimage.2023.120353] [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: 04/06/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023] Open
Abstract
The simultaneous acquisition of electroencephalography and functional magnetic resonance imaging (EEG-fMRI) allows the complementary study of the brain's electrophysiology and hemodynamics with high temporal and spatial resolution. One application with great potential is neurofeedback training of targeted brain activity, based on the real-time analysis of the EEG and/or fMRI signals. This depends on the ability to reduce in real time the severe artifacts affecting the EEG signal acquired with fMRI, mainly the gradient and pulse artifacts. A few methods have been proposed for this purpose, but they are either slow, hardware-dependent, publicly unavailable, or proprietary software. Here, we present a fully open-source and publicly available tool for real-time EEG artifact reduction in simultaneous EEG-fMRI recordings that is fast and applicable to any hardware. Our tool is integrated in the Python toolbox NeuXus for real-time EEG processing and adapts to a real-time scenario well-established artifact average subtraction methods combined with a long short-term memory network for R peak detection. We benchmarked NeuXus on three different datasets, in terms of artifact power reduction and background signal preservation in resting state, alpha-band power reactivity to eyes closure, and event-related desynchronization during motor imagery. We showed that NeuXus performed at least as well as the only available real-time tool for conventional hardware setups (BrainVision's RecView) and a well-established offline tool (EEGLAB's FMRIB plugin). We also demonstrated NeuXus' real-time ability by reporting execution times under 250 ms. In conclusion, we present and validate the first fully open-source and hardware-independent solution for real-time artifact reduction in simultaneous EEG-fMRI studies.
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Affiliation(s)
- Gustavo Caetano
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Inês Esteves
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Athanasios Vourvopoulos
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Mathis Fleury
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal.
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22
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Dehghani A, Soltanian-Zadeh H, Hossein-Zadeh GA. Neural modulation enhancement using connectivity-based EEG neurofeedback with simultaneous fMRI for emotion regulation. Neuroimage 2023; 279:120320. [PMID: 37586444 DOI: 10.1016/j.neuroimage.2023.120320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 08/18/2023] Open
Abstract
Emotion regulation plays a key role in human behavior and overall well-being. Neurofeedback is a non-invasive self-brain training technique used for emotion regulation to enhance brain function and treatment of mental disorders through behavioral changes. Previous neurofeedback research often focused on using activity from a single brain region as measured by fMRI or power from one or two EEG electrodes. In a new study, we employed connectivity-based EEG neurofeedback through recalling positive autobiographical memories and simultaneous fMRI to upregulate positive emotion. In our novel approach, the feedback was determined by the coherence of EEG electrodes rather than the power of one or two electrodes. We compared the efficiency of this connectivity-based neurofeedback to traditional activity-based neurofeedback through multiple experiments. The results showed that connectivity-based neurofeedback effectively improved BOLD signal change and connectivity in key emotion regulation regions such as the amygdala, thalamus, and insula, and increased EEG frontal asymmetry, which is a biomarker for emotion regulation and treatment of mental disorders such as PTSD, anxiety, and depression and coherence among EEG channels. The psychometric evaluations conducted both before and after the neurofeedback experiments revealed that participants demonstrated improvements in enhancing positive emotions and reducing negative emotions when utilizing connectivity-based neurofeedback, as compared to traditional activity-based and sham neurofeedback approaches. These findings suggest that connectivity-based neurofeedback may be a superior method for regulating emotions and could be a useful alternative therapy for mental disorders, providing individuals with greater control over their brain and mental functions.
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Affiliation(s)
- Amin Dehghani
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Hamid Soltanian-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, USA
| | - Gholam-Ali Hossein-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
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23
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van de Velden D, Stier C, Kotikalapudi R, Heide EC, Garnica-Agudelo D, Focke NK. Comparison of Resting-State EEG Network Analyses With and Without Parallel MRI in Genetic Generalized Epilepsy. Brain Topogr 2023; 36:750-765. [PMID: 37354244 PMCID: PMC10415462 DOI: 10.1007/s10548-023-00977-6] [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: 07/20/2022] [Accepted: 06/12/2023] [Indexed: 06/26/2023]
Abstract
Genetic generalized epilepsy (GGE) is conceptualized as a brain disorder involving distributed bilateral networks. To study these networks, simultaneous EEG-fMRI measurements can be used. However, inside-MRI EEG suffers from strong MR-related artifacts; it is not established whether EEG-based metrics in EEG-fMRI resting-state measurements are suitable for the analysis of group differences at source-level. We evaluated the impact of the inside-MR measurement condition on statistical group comparisons of EEG on source-level power and functional connectivity in patients with GGE versus healthy controls. We studied the cross-modal spatial relation of statistical group differences in seed-based FC derived from EEG and parallel fMRI. We found a significant increase in power and a frequency-specific change in functional connectivity for the inside MR-scanner compared to the outside MR-scanner condition. For power, we found reduced group difference between GGE and controls both in terms of statistical significance as well as effect size. Group differences for ImCoh remained similar both in terms of statistical significance as well as effect size. We found increased seed-based FC for GGE patients from the thalamus to the precuneus cortex region in fMRI, and in the theta band of simultaneous EEG. Our findings suggest that the analysis of EEG functional connectivity based on ImCoh is suitable for MR-EEG, and that relative group difference in a comparison of patients with GGE against controls are preserved. Spatial correspondence of seed-based FC group differences between the two modalities was found for the thalamus.
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Affiliation(s)
- Daniel van de Velden
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany.
| | - Christina Stier
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University Medical Center Tübingen, University of Tübingen, 72076, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University Medical Center Tübingen, University of Tübingen, 72076, Tübingen, Germany
- Clinic for Neurology, University Medical Center Essen/University Duisburg-Essen, 45147, Essen, Germany
| | - Ev-Christin Heide
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - David Garnica-Agudelo
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Niels K Focke
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany.
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University Medical Center Tübingen, University of Tübingen, 72076, Tübingen, Germany.
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24
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Telesford QK, Gonzalez-Moreira E, Xu T, Tian Y, Colcombe SJ, Cloud J, Russ BE, Falchier A, Nentwich M, Madsen J, Parra LC, Schroeder CE, Milham MP, Franco AR. An open-access dataset of naturalistic viewing using simultaneous EEG-fMRI. Sci Data 2023; 10:554. [PMID: 37612297 PMCID: PMC10447527 DOI: 10.1038/s41597-023-02458-8] [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: 03/20/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023] Open
Abstract
In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23-51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.
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Affiliation(s)
- Qawi K Telesford
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Eduardo Gonzalez-Moreira
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Yiwen Tian
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Stanley J Colcombe
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Jessica Cloud
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Brian E Russ
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Arnaud Falchier
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Maximilian Nentwich
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Jens Madsen
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Lucas C Parra
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Charles E Schroeder
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Departments of Psychiatry and Neurology, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Michael P Milham
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Alexandre R Franco
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA.
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25
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Nebe S, Reutter M, Baker DH, Bölte J, Domes G, Gamer M, Gärtner A, Gießing C, Gurr C, Hilger K, Jawinski P, Kulke L, Lischke A, Markett S, Meier M, Merz CJ, Popov T, Puhlmann LMC, Quintana DS, Schäfer T, Schubert AL, Sperl MFJ, Vehlen A, Lonsdorf TB, Feld GB. Enhancing precision in human neuroscience. eLife 2023; 12:e85980. [PMID: 37555830 PMCID: PMC10411974 DOI: 10.7554/elife.85980] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 07/23/2023] [Indexed: 08/10/2023] Open
Abstract
Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.
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Affiliation(s)
- Stephan Nebe
- Zurich Center for Neuroeconomics, Department of Economics, University of ZurichZurichSwitzerland
| | - Mario Reutter
- Department of Psychology, Julius-Maximilians-UniversityWürzburgGermany
| | - Daniel H Baker
- Department of Psychology and York Biomedical Research Institute, University of YorkYorkUnited Kingdom
| | - Jens Bölte
- Institute for Psychology, University of Münster, Otto-Creuzfeldt Center for Cognitive and Behavioral NeuroscienceMünsterGermany
| | - Gregor Domes
- Department of Biological and Clinical Psychology, University of TrierTrierGermany
- Institute for Cognitive and Affective NeuroscienceTrierGermany
| | - Matthias Gamer
- Department of Psychology, Julius-Maximilians-UniversityWürzburgGermany
| | - Anne Gärtner
- Faculty of Psychology, Technische Universität DresdenDresdenGermany
| | - Carsten Gießing
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University of OldenburgOldenburgGermany
| | - Caroline Gurr
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe UniversityFrankfurtGermany
- Brain Imaging Center, Goethe UniversityFrankfurtGermany
| | - Kirsten Hilger
- Department of Psychology, Julius-Maximilians-UniversityWürzburgGermany
- Department of Psychology, Psychological Diagnostics and Intervention, Catholic University of Eichstätt-IngolstadtEichstättGermany
| | - Philippe Jawinski
- Department of Psychology, Humboldt-Universität zu BerlinBerlinGermany
| | - Louisa Kulke
- Department of Developmental with Educational Psychology, University of BremenBremenGermany
| | - Alexander Lischke
- Department of Psychology, Medical School HamburgHamburgGermany
- Institute of Clinical Psychology and Psychotherapy, Medical School HamburgHamburgGermany
| | - Sebastian Markett
- Department of Psychology, Humboldt-Universität zu BerlinBerlinGermany
| | - Maria Meier
- Department of Psychology, University of KonstanzKonstanzGermany
- University Psychiatric Hospitals, Child and Adolescent Psychiatric Research Department (UPKKJ), University of BaselBaselSwitzerland
| | - Christian J Merz
- Department of Cognitive Psychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University BochumBochumGermany
| | - Tzvetan Popov
- Department of Psychology, Methods of Plasticity Research, University of ZurichZurichSwitzerland
| | - Lara MC Puhlmann
- Leibniz Institute for Resilience ResearchMainzGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Daniel S Quintana
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- NevSom, Department of Rare Disorders & Disabilities, Oslo University HospitalOsloNorway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT), University of OsloOsloNorway
| | - Tim Schäfer
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe UniversityFrankfurtGermany
- Brain Imaging Center, Goethe UniversityFrankfurtGermany
| | | | - Matthias FJ Sperl
- Department of Clinical Psychology and Psychotherapy, University of GiessenGiessenGermany
- Center for Mind, Brain and Behavior, Universities of Marburg and GiessenGiessenGermany
| | - Antonia Vehlen
- Department of Biological and Clinical Psychology, University of TrierTrierGermany
| | - Tina B Lonsdorf
- Department of Systems Neuroscience, University Medical Center Hamburg-EppendorfHamburgGermany
- Department of Psychology, Biological Psychology and Cognitive Neuroscience, University of BielefeldBielefeldGermany
| | - Gordon B Feld
- Department of Clinical Psychology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
- Department of Psychology, Heidelberg UniversityHeidelbergGermany
- Department of Addiction Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
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26
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Kaptan M, Horn U, Vannesjo SJ, Mildner T, Weiskopf N, Finsterbusch J, Brooks JCW, Eippert F. Reliability of resting-state functional connectivity in the human spinal cord: Assessing the impact of distinct noise sources. Neuroimage 2023; 275:120152. [PMID: 37142169 PMCID: PMC10262064 DOI: 10.1016/j.neuroimage.2023.120152] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 04/20/2023] [Accepted: 05/01/2023] [Indexed: 05/06/2023] Open
Abstract
The investigation of spontaneous fluctuations of the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord, where it has stimulated interest from a clinical perspective. A number of resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated robust functional connectivity between the time series of BOLD fluctuations in bilateral dorsal horns and between those in bilateral ventral horns, in line with the functional neuroanatomy of the spinal cord. A necessary step prior to extension to clinical studies is assessing the reliability of such resting-state signals, which we aimed to do here in a group of 45 healthy young adults at the clinically prevalent field strength of 3T. When investigating connectivity in the entire cervical spinal cord, we observed fair to good reliability for dorsal-dorsal and ventral-ventral connectivity, whereas reliability was poor for within- and between-hemicord dorsal-ventral connectivity. Considering how prone spinal cord fMRI is to noise, we extensively investigated the impact of distinct noise sources and made two crucial observations: removal of physiological noise led to a reduction in functional connectivity strength and reliability - due to the removal of stable and participant-specific noise patterns - whereas removal of thermal noise considerably increased the detectability of functional connectivity without a clear influence on reliability. Finally, we also assessed connectivity within spinal cord segments and observed that while the pattern of connectivity was similar to that of whole cervical cord, reliability at the level of single segments was consistently poor. Taken together, our results demonstrate the presence of reliable resting-state functional connectivity in the human spinal cord even after thoroughly accounting for physiological and thermal noise, but at the same time urge caution if focal changes in connectivity (e.g. due to segmental lesions) are to be studied, especially in a longitudinal manner.
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Affiliation(s)
- Merve Kaptan
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Ulrike Horn
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - S Johanna Vannesjo
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
| | - Toralf Mildner
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Leipzig, Germany
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonathan C W Brooks
- School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), Norwich, UK
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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27
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Levitt J, Yang Z, Williams SD, Lütschg Espinosa SE, Garcia-Casal A, Lewis LD. EEG-LLAMAS: A low-latency neurofeedback platform for artifact reduction in EEG-fMRI. Neuroimage 2023; 273:120092. [PMID: 37028736 PMCID: PMC10202030 DOI: 10.1016/j.neuroimage.2023.120092] [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: 10/31/2022] [Revised: 03/02/2023] [Accepted: 04/04/2023] [Indexed: 04/08/2023] Open
Abstract
Simultaneous EEG-fMRI is a powerful multimodal technique for imaging the brain, but its use in neurofeedback experiments has been limited by EEG noise caused by the MRI environment. Neurofeedback studies typically require analysis of EEG in real time, but EEG acquired inside the scanner is heavily contaminated with ballistocardiogram (BCG) artifact, a high-amplitude artifact locked to the cardiac cycle. Although techniques for removing BCG artifacts do exist, they are either not suited to real-time, low-latency applications, such as neurofeedback, or have limited efficacy. We propose and validate a new open-source artifact removal software called EEG-LLAMAS (Low Latency Artifact Mitigation Acquisition Software), which adapts and advances existing artifact removal techniques for low-latency experiments. We first used simulations to validate LLAMAS in data with known ground truth. We found that LLAMAS performed better than the best publicly-available real-time BCG removal technique, optimal basis sets (OBS), in terms of its ability to recover EEG waveforms, power spectra, and slow wave phase. To determine whether LLAMAS would be effective in practice, we then used it to conduct real-time EEG-fMRI recordings in healthy adults, using a steady state visual evoked potential (SSVEP) task. We found that LLAMAS was able to recover the SSVEP in real time, and recovered the power spectra collected outside the scanner better than OBS. We also measured the latency of LLAMAS during live recordings, and found that it introduced a lag of less than 50 ms on average. The low latency of LLAMAS, coupled with its improved artifact reduction, can thus be effectively used for EEG-fMRI neurofeedback. A limitation of the method is its use of a reference layer, a piece of EEG equipment which is not commercially available, but can be assembled in-house. This platform enables closed-loop experiments which previously would have been prohibitively difficult, such as those that target short-duration EEG events, and is shared openly with the neuroscience community.
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Affiliation(s)
- Joshua Levitt
- Department of Biomedical Engineering, Boston University, USA
| | - Zinong Yang
- Department of Biomedical Engineering, Boston University, USA; Graduate Program of Neuroscience, Boston University, USA
| | | | | | | | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, USA; Institute for Medical Engineering and Sciences, Department of Electrical Engineering and Computer Science, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA.
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28
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Rassler B, Blinowska K, Kaminski M, Pfurtscheller G. Analysis of Respiratory Sinus Arrhythmia and Directed Information Flow between Brain and Body Indicate Different Management Strategies of fMRI-Related Anxiety. Biomedicines 2023; 11:biomedicines11041028. [PMID: 37189642 DOI: 10.3390/biomedicines11041028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
Background: Respiratory sinus arrhythmia (RSA) denotes decrease of cardiac beat-to-beat intervals (RRI) during inspiration and RRI increase during expiration, but an inverse pattern (termed negative RSA) was also found in healthy humans with elevated anxiety. It was detected using wave-by-wave analysis of cardiorespiratory rhythms and was considered to reflect a strategy of anxiety management involving the activation of a neural pacemaker. Results were consistent with slow breathing, but contained uncertainty at normal breathing rates (0.2–0.4 Hz). Objectives and methods: We combined wave-by-wave analysis and directed information flow analysis to obtain information on anxiety management at higher breathing rates. We analyzed cardiorespiratory rhythms and blood oxygen level-dependent (BOLD) signals from the brainstem and cortex in 10 healthy fMRI participants with elevated anxiety. Results: Three subjects with slow respiratory, RRI, and neural BOLD oscillations showed 57 ± 26% negative RSA and significant anxiety reduction by 54 ± 9%. Six participants with breathing rate of ~0.3 Hz showed 41 ± 16% negative RSA and weaker anxiety reduction. They presented significant information flow from RRI to respiration and from the middle frontal cortex to the brainstem, which may result from respiration-entrained brain oscillations, indicating another anxiety management strategy. Conclusion: The two analytical approaches applied here indicate at least two different anxiety management strategies in healthy subjects.
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29
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Statistical inference on the significance of rows and columns for matrix-valued data in an additive model. TEST-SPAIN 2023. [DOI: 10.1007/s11749-023-00852-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
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30
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Liu Y, Zhang Y, Jiang Z, Kong W, Zou L. Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG-fMRI Investigation. Brain Sci 2023; 13:485. [PMID: 36979295 PMCID: PMC10046863 DOI: 10.3390/brainsci13030485] [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: 02/22/2023] [Revised: 03/06/2023] [Accepted: 03/08/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND It is crucial to understand the neural feedback mechanisms and the cognitive decision-making of the brain during the processing of rewards. Here, we report the first attempt for a simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) study in a gambling task by utilizing tensor decomposition. METHODS First, the single-subject EEG data are represented as a third-order spectrogram tensor to extract frequency features. Next, the EEG and fMRI data are jointly decomposed into a superposition of multiple sources characterized by space-time-frequency profiles using coupled matrix tensor factorization (CMTF). Finally, graph-structured clustering is used to select the most appropriate model according to four quantitative indices. RESULTS The results clearly show that not only are the regions of interest (ROIs) found in other literature activated, but also the olfactory cortex and fusiform gyrus which are usually ignored. It is found that regions including the orbitofrontal cortex and insula are activated for both winning and losing stimuli. Meanwhile, regions such as the superior orbital frontal gyrus and anterior cingulate cortex are activated upon winning stimuli, whereas the inferior frontal gyrus, cingulate cortex, and medial superior frontal gyrus are activated upon losing stimuli. CONCLUSION This work sheds light on the reward-processing progress, provides a deeper understanding of brain function, and opens a new avenue in the investigation of neurovascular coupling via CMTF.
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Affiliation(s)
- Yuchao Liu
- School of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China
| | - Yin Zhang
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Zhongyi Jiang
- School of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China
| | - Wanzeng Kong
- College of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou 310018, China
| | - Ling Zou
- School of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou 310018, China
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31
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Qin Y, Jiang S, Xiong S, Li S, Fu Q, Yang L, Du P, Luo C, Yao D. Unbalance between working memory task-activation and task-deactivation networks in epilepsy: Simultaneous EEG-fMRI study. J Neurosci Res 2023; 101:1188-1199. [PMID: 36866516 DOI: 10.1002/jnr.25183] [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: 08/03/2022] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 03/04/2023]
Abstract
Working memory (WM) is a cognitive function involving emergent properties of theta oscillations and large-scale network interactions. The synchronization of WM task-related networks in the brain enhanced WM performance. However, how these networks regulate WM processing is not well known, and the alteration of the interaction among these networks may play an important role in patients with cognitive dysfunction. In this study, we used simultaneous EEG-fMRI to examine the features of theta oscillations and the functional interactions among activation/deactivation networks during the n-back WM task in patients with idiopathic generalized epilepsy (IGE). The results showed that there was more enhancement of frontal theta power along with WM load increase in IGE, and the theta power was positively correlated with the accuracy of the WM tasks. Moreover, fMRI activations/deactivations correlated with n-back tasks were estimated, and we found that the IGE group had increased and widespread activations in high-load WM tasks, including the frontoparietal activation network and task-related deactivation areas, such as the default mode network and primary visual and auditory networks. In addition, the network connectivity results demonstrated decreased counteraction between the activation network and deactivation network, and the counteraction was correlated with the higher theta power in IGE. These results indicated the important role of the interactions between activation and deactivation networks during the WM process, and the unbalance among them may indicate the pathophysiological mechanism of cognitive dysfunction in generalized epilepsy.
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Affiliation(s)
- Yun Qin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Siwei Xiong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Sipei Li
- Glasgow College, University of Electronic Science and Technology of China, Chengdu, China
| | - Qiankun Fu
- Glasgow College, University of Electronic Science and Technology of China, Chengdu, China
| | - Lili Yang
- Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Peishan Du
- Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China
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32
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Pfurtscheller G, Kaminski M, J Blinowska K, Rassler B, Schwarz G, Klimesch W. Respiration-entrained brain oscillations in healthy fMRI participants with high anxiety. Sci Rep 2023; 13:2380. [PMID: 36765092 PMCID: PMC9918542 DOI: 10.1038/s41598-023-29482-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/06/2023] [Indexed: 02/12/2023] Open
Abstract
Brain-body interactions can be studied by using directed coupling measurements of fMRI oscillations in the low (0.1-0.2 Hz) and high frequency bands (HF; 0.2-0.4 Hz). Recently, a preponderance of oscillations in the information flow between the brainstem and the prefrontal cortex at around 0.15/0.16 Hz was shown. The goal of this study was to investigate the information flow between BOLD-, respiratory-, and heart beat-to-beat interval (RRI) signals in the HF band in healthy subjects with high anxiety during fMRI examinations. A multivariate autoregressive model was concurrently applied to the BOLD signals from the middle frontal gyrus (MFG), precentral gyrus and the brainstem, as well as to respiratory and RRI signals. Causal coupling between all signals was determined using the Directed Transfer Function (DTF). We found a salience of fast respiratory waves with a period of 3.1 s (corresponding to ~ 0.32 Hz) and a highly significant (p < 0.001) top-down information-flow from BOLD oscillations in the MFG to the brainstem. Additionally, there was a significant (p < 0.01) information flow from RRI to respiratory oscillations. We speculate that brain oscillations around 0.32 Hz, triggered by nasal breathing, are projected downwards to the brainstem. Particularly interesting is the driving force of cardiac to respiratory waves with a ratio of 1:1 or 1:2. These results support the binary hierarchy model with preferred respiratory frequencies at 0.32 Hz and 0.16 Hz.
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Affiliation(s)
- Gert Pfurtscheller
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria
| | - Maciej Kaminski
- Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093, Warsaw, Poland.
| | - Katarzyna J Blinowska
- Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093, Warsaw, Poland
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4 St., 02-109, Warsaw, Poland
| | - Beate Rassler
- Carl-Ludwig-Institute of Physiology, University of Leipzig, Leipzig, Germany
| | - Gerhard Schwarz
- Department of Anaesthesiology and Intensive Care Medicine, Medical University of Graz, Graz, Austria
| | - Wolfgang Klimesch
- Centre of Cognitive Neuroscience, University of Salzburg, Salzburg, Austria
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Dehghani A, Soltanian-Zadeh H, Hossein-Zadeh GA. Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback. Front Hum Neurosci 2023; 16:988890. [PMID: 36684847 PMCID: PMC9853008 DOI: 10.3389/fnhum.2022.988890] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 12/13/2022] [Indexed: 01/09/2023] Open
Abstract
Despite the existence of several emotion regulation studies using neurofeedback, interactions among a small number of regions were evaluated, and therefore, further investigation is needed to understand the interactions of the brain regions involved in emotion regulation. We implemented electroencephalography (EEG) neurofeedback with simultaneous functional magnetic resonance imaging (fMRI) using a modified happiness-inducing task through autobiographical memories to upregulate positive emotion. Then, an explorative analysis of whole brain regions was done to understand the effect of neurofeedback on brain activity and the interaction of whole brain regions involved in emotion regulation. The participants in the control and experimental groups were asked to do emotion regulation while viewing positive images of autobiographical memories and getting sham or real (based on alpha asymmetry) EEG neurofeedback, respectively. The proposed multimodal approach quantified the effects of EEG neurofeedback in changing EEG alpha power, fMRI blood oxygenation level-dependent (BOLD) activity of prefrontal, occipital, parietal, and limbic regions (up to 1.9% increase), and functional connectivity in/between prefrontal, parietal, limbic system, and insula in the experimental group. New connectivity links were identified by comparing the brain functional connectivity between experimental conditions (Upregulation and View blocks) and also by comparing the brain connectivity of the experimental and control groups. Psychometric assessments confirmed significant changes in positive and negative mood states in the experimental group by neurofeedback. Based on the exploratory analysis of activity and connectivity among all brain regions involved in emotion regions, we found significant BOLD and functional connectivity increases due to EEG neurofeedback in the experimental group, but no learning effect was observed in the control group. The results reveal several new connections among brain regions as a result of EEG neurofeedback which can be justified according to emotion regulation models and the role of those regions in emotion regulation and recalling positive autobiographical memories.
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Affiliation(s)
- Amin Dehghani
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States,*Correspondence: Amin Dehghani, ,
| | - Hamid Soltanian-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,Medical Image Analysis Lab, Department of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Gholam-Ali Hossein-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
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Gallego-Rudolf J, Corsi-Cabrera M, Concha L, Ricardo-Garcell J, Pasaye-Alcaraz E. Preservation of EEG spectral power features during simultaneous EEG-fMRI. Front Neurosci 2022; 16:951321. [PMID: 36620439 PMCID: PMC9816433 DOI: 10.3389/fnins.2022.951321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction Electroencephalographic (EEG) data quality is severely compromised when recorded inside the magnetic resonance (MR) environment. Here we characterized the impact of the ballistocardiographic (BCG) artifact on resting-state EEG spectral properties and compared the effectiveness of seven common BCG correction methods to preserve EEG spectral features. We also assessed if these methods retained posterior alpha power reactivity to an eyes closure-opening (EC-EO) task and compared the results from EEG-informed fMRI analysis using different BCG correction approaches. Method Electroencephalographic data from 20 healthy young adults were recorded outside the MR environment and during simultaneous fMRI acquisition. The gradient artifact was effectively removed from EEG-fMRI acquisitions using Average Artifact Subtraction (AAS). The BCG artifact was corrected with seven methods: AAS, Optimal Basis Set (OBS), Independent Component Analysis (ICA), OBS followed by ICA, AAS followed by ICA, PROJIC-AAS and PROJIC-OBS. EEG signal preservation was assessed by comparing the spectral power of traditional frequency bands from the corrected rs-EEG-fMRI data with the data recorded outside the scanner. We then assessed the preservation of posterior alpha functional reactivity by computing the ratio between the EC and EO conditions during the EC-EO task. EEG-informed fMRI analysis of the EC-EO task was performed using alpha power-derived BOLD signal predictors obtained from the EEG signals corrected with different methods. Results The BCG artifact caused significant distortions (increased absolute power, altered relative power) across all frequency bands. Artifact residuals/signal losses were present after applying all correction methods. The EEG reactivity to the EC-EO task was better preserved with ICA-based correction approaches, particularly when using ICA feature extraction to isolate alpha power fluctuations, which allowed to accurately predict hemodynamic signal fluctuations during the EEG-informed fMRI analysis. Discussion Current software solutions for the BCG artifact problem offer limited efficiency to preserve the EEG spectral power properties using this particular EEG setup. The state-of-the-art approaches tested here can be further refined and should be combined with hardware implementations to better preserve EEG signal properties during simultaneous EEG-fMRI. Existing and novel BCG artifact correction methods should be validated by evaluating signal preservation of both ERPs and spontaneous EEG spectral power.
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Affiliation(s)
- Jonathan Gallego-Rudolf
- Unidad de Resonancia Magnética, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - María Corsi-Cabrera
- Laboratorio de Sueño, Facultad de Psicología, Universidad Nacional Autónoma de México, Mexico City, Mexico
- Unidad de Neurodesarrollo, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Luis Concha
- Laboratorio de Conectividad Cerebral, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Josefina Ricardo-Garcell
- Unidad de Neurodesarrollo, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Erick Pasaye-Alcaraz
- Unidad de Resonancia Magnética, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico
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35
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Uji M, Tamaki M. Sleep, learning, and memory in human research using noninvasive neuroimaging techniques. Neurosci Res 2022; 189:66-74. [PMID: 36572251 DOI: 10.1016/j.neures.2022.12.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 11/25/2022] [Accepted: 12/18/2022] [Indexed: 12/24/2022]
Abstract
An accumulating body of evidence indicates that sleep is beneficial for learning and memory. Task performance improves significantly after a period that includes sleep, whereas a lack of sleep nullifies or impairs such improvements. Our current knowledge about sleep's role in learning and memory has been obtained based on studies that were conducted in both animal models and human subjects. Nevertheless, how sleep promotes learning and memory in humans is not fully understood. In this review, we overview our current understating of how sleep may contribute to learning and memory, covering different roles of non-rapid eye movement and rapid eye movement sleep. We then discuss cutting-edge advanced techniques that are currently available, including simultaneous functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) and simultaneous functional magnetic resonance spectroscopy (fMRS) and EEG measurements, and evaluate how these may contribute to advance the understanding of the role of sleep in human cognition. We also highlight the current limitations and challenges using these methods and discuss ways that may allow us to overcome these limitations.
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Affiliation(s)
- Makoto Uji
- RIKEN Center for Brain Science, Saitama 3510198, Japan
| | - Masako Tamaki
- RIKEN Center for Brain Science, Saitama 3510198, Japan; RIKEN Cluster for Pioneering Research, Saitama 3510198, Japan.
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36
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Ilhan-Bayrakcı M, Cabral-Calderin Y, Bergmann TO, Tüscher O, Stroh A. Individual slow wave events give rise to macroscopic fMRI signatures and drive the strength of the BOLD signal in human resting-state EEG-fMRI recordings. Cereb Cortex 2022; 32:4782-4796. [PMID: 35094045 PMCID: PMC9627041 DOI: 10.1093/cercor/bhab516] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 12/08/2021] [Accepted: 12/09/2021] [Indexed: 08/19/2024] Open
Abstract
The slow wave state is a general state of quiescence interrupted by sudden bursts of activity or so-called slow wave events (SWEs). Recently, the relationship between SWEs and blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals was assessed in rodent models which revealed cortex-wide BOLD activation. However, it remains unclear which macroscopic signature corresponds to these specific neurophysiological events in the human brain. Therefore, we analyzed simultaneous electroencephalographic (EEG)-fMRI data during human non-REM sleep. SWEs individually detected in the EEG data were used as predictors in event-related fMRI analyses to examine the relationship between SWEs and fMRI signals. For all 10 subjects we identified significant changes in BOLD activity associated with SWEs covering substantial parts of the gray matter. As demonstrated in rodents, we observed a direct relation of a neurophysiological event to specific BOLD activation patterns. We found a correlation between the number of SWEs and the spatial extent of these BOLD activation patterns and discovered that the amplitude of the BOLD response strongly depends on the SWE amplitude. As altered SWE propagation has recently been found in neuropsychiatric diseases, it is critical to reveal the brain's physiological slow wave state networks to potentially establish early imaging biomarkers for various diseases long before disease onset.
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Affiliation(s)
- Merve Ilhan-Bayrakcı
- Systemic Mechanisms of Resilience, Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
| | - Yuranny Cabral-Calderin
- Neural and Environmental Rhythms, Max Planck Institute for Empirical Aesthetics, 60322 Frankfurt, Germany
| | - Til Ole Bergmann
- Systemic Mechanisms of Resilience, Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Oliver Tüscher
- Systemic Mechanisms of Resilience, Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Albrecht Stroh
- Systemic Mechanisms of Resilience, Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
- Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
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Agrawal S, Chinnadurai V, Sharma R. Hemodynamic functional connectivity optimization of frequency EEG microstates enables attention LSTM framework to classify distinct temporal cortical communications of different cognitive tasks. Brain Inform 2022; 9:25. [PMID: 36219346 PMCID: PMC9554110 DOI: 10.1186/s40708-022-00173-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 09/28/2022] [Indexed: 11/24/2022] Open
Abstract
Temporal analysis of global cortical communication of cognitive tasks in coarse EEG information is still challenging due to the underlying complex neural mechanisms. This study proposes an attention-based time-series deep learning framework that processes fMRI functional connectivity optimized quasi-stable frequency microstates for classifying distinct temporal cortical communications of the cognitive task. Seventy volunteers were subjected to visual target detection tasks, and their electroencephalogram (EEG) and functional MRI (fMRI) were acquired simultaneously. At first, the acquired EEG information was preprocessed and bandpass to delta, theta, alpha, beta, and gamma bands and then subjected to quasi-stable frequency-microstate estimation. Subsequently, time-series elicitation of each frequency microstates is optimized with graph theory measures of simultaneously eliciting fMRI functional connectivity between frontal, parietal, and temporal cortices. The distinct neural mechanisms associated with each optimized frequency-microstate were analyzed using microstate-informed fMRI. Finally, these optimized, quasi-stable frequency microstates were employed to train and validate the attention-based Long Short-Term Memory (LSTM) time-series architecture for classifying distinct temporal cortical communications of the target from other cognitive tasks. The temporal, sliding input sampling windows were chosen between 180 to 750 ms/segment based on the stability of transition probabilities of the optimized microstates. The results revealed 12 distinct frequency microstates capable of deciphering target detections' temporal cortical communications from other task engagements. Particularly, fMRI functional connectivity measures of target engagement were observed significantly correlated with the right-diagonal delta (r = 0.31), anterior-posterior theta (r = 0.35), left-right theta (r = - 0.32), alpha (r = - 0.31) microstates. Further, neuro-vascular information of microstate-informed fMRI analysis revealed the association of delta/theta and alpha/beta microstates with cortical communications and local neural processing, respectively. The classification accuracies of the attention-based LSTM were higher than the traditional LSTM architectures, particularly the frameworks that sampled the EEG data with a temporal width of 300 ms/segment. In conclusion, the study demonstrates reliable temporal classifications of global cortical communication of distinct tasks using an attention-based LSTM utilizing fMRI functional connectivity optimized quasi-stable frequency microstates.
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Affiliation(s)
- Swati Agrawal
- Institute of Nuclear Medicine and Allied Sciences, Lucknow Road, Timarpur, Delhi, 110054, India
- Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi, 110042, India
| | - Vijayakumar Chinnadurai
- Institute of Nuclear Medicine and Allied Sciences, Lucknow Road, Timarpur, Delhi, 110054, India.
| | - Rinku Sharma
- Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi, 110042, India
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Maki Y, Natsume J, Ito Y, Okai Y, Bagarinao E, Yamamoto H, Ogaya S, Takeuchi T, Fukasawa T, Sawamura F, Mitsumatsu T, Maesawa S, Saito R, Takahashi Y, Kidokoro H. Involvement of the Thalamus, Hippocampus, and Brainstem in Hypsarrhythmia of West Syndrome: Simultaneous Recordings of Electroencephalography and fMRI Study. AJNR Am J Neuroradiol 2022; 43:1502-1507. [PMID: 36137665 PMCID: PMC9575537 DOI: 10.3174/ajnr.a7646] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 07/27/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE West syndrome is a developmental and epileptic encephalopathy characterized by epileptic spasms, neurodevelopmental regression, and a specific EEG pattern called hypsarrhythmia. Our aim was to investigate the brain activities related to hypsarrhythmia at onset and focal epileptiform discharges in the remote period in children with West syndrome using simultaneous electroencephalography and fMRI recordings. MATERIALS AND METHODS Fourteen children with West syndrome underwent simultaneous electroencephalography and fMRI at the onset of West syndrome. Statistically significant blood oxygen level-dependent responses related to hypsarrhythmia were analyzed using an event-related design of 4 hemodynamic response functions with peaks at 3, 5, 7, and 9 seconds after the onset of each event. Six of 14 children had focal epileptiform discharges after treatment and underwent simultaneous electroencephalography and fMRI from 12 to 25 months of age. RESULTS At onset, positive blood oxygen level-dependent responses were seen in the brainstem (14/14 patients), thalami (13/14), basal ganglia (13/14), and hippocampi (13/14), in addition to multiple cerebral cortices. Group analysis using hemodynamic response functions with peaks at 3, 5, and 7 seconds showed positive blood oxygen level-dependent responses in the brainstem, thalamus, and hippocampus, while positive blood oxygen level-dependent responses in multiple cerebral cortices were seen using hemodynamic response functions with peaks at 5 and 7 seconds. In the remote period, 3 of 6 children had focal epileptiform discharge-related positive blood oxygen level-dependent responses in the thalamus, hippocampus, and brainstem. CONCLUSIONS Positive blood oxygen level-dependent responses with hypsarrhythmia appeared in the brainstem, thalamus, and hippocampus on earlier hemodynamic response functions than the cerebral cortices, suggesting the propagation of epileptogenic activities from the deep brain structures to the neocortices. Activation of the hippocampus, thalamus, and brainstem was still seen in half of the patients with focal epileptiform discharges after adrenocorticotropic hormone therapy.
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Affiliation(s)
- Y Maki
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
| | - J Natsume
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
- Developmental Disability Medicine (J.N.)
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
| | - Y Ito
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
- Department of Pediatrics (Y.I.), Aichi Prefectural Mikawa Aoitori Medical and Rehabilitation Center, Okazaki, Japan
| | - Y Okai
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
- Department of Pediatric Neurology (Y.O.), Toyota Municipal Child Development Center, Toyota, Japan
| | - E Bagarinao
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
| | - H Yamamoto
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
| | - S Ogaya
- Department of Pediatric Neurology (S.O.), Aichi Developmental Disability Center Central Hospital, Kasugai, Japan
| | - T Takeuchi
- Department of Pediatrics (T.T.), Japanese Red Cross Nagoya First Hospital
| | - T Fukasawa
- Nagoya, Japan; and Department of Pediatrics (T.F.), Anjo Kosei Hospital, Anjo, Japan
| | - F Sawamura
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
| | - T Mitsumatsu
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
| | - S Maesawa
- Neurosurgery (S.M., R.S.), Nagoya University Graduate School of Medicine, Nagoya, Japan
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
| | - R Saito
- Neurosurgery (S.M., R.S.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Y Takahashi
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
| | - H Kidokoro
- From the Departments of Pediatrics (Y.M., J.N., Y.I., Y.O., H.Y., F.S., T.M., Y.T., H.K.)
- Brain and Mind Research Center (J.N., Y.I., Y.O., E.B., H.Y., S.M., H.K.), Nagoya University, Nagoya, Japan
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Abstract
In resting state functional magnetic resonance imaging (fMRI), areas showing coherent hemodynamic fluctuations across the brain are operationally defined to be functionally connected. However, it is unknown how the activity of single units residing within a voxel contributes to this network structure. Here we demonstrate a shared but restricted pattern of functional connectivity among neighboring neurons residing in functionally defined face patches. Unexpectedly, such neurons also exhibited a prominent inverse correlation with thalamic structures and brainstem neuromodulatory centers. Single unit maps differed from analogous maps obtained with local field potentials and seed-based fMRI. These findings suggest that during rest, individual cortical neurons have a restricted set of functional connections, which is governed in part by anatomical projections and in part by neuromodulation. The brain is a highly organized, dynamic system whose network architecture is often assessed through resting functional magnetic resonance imaging (fMRI) functional connectivity. The functional interactions between brain areas, including those observed during rest, are assumed to stem from the collective influence of action potentials carried by long-range neural projections. However, the contribution of individual neurons to brain-wide functional connectivity has not been systematically assessed. Here we developed a method to concurrently measure and compare the spiking activity of local neurons with fMRI signals measured across the brain during rest. We recorded spontaneous activity from neural populations in cortical face patches in the macaque during fMRI scanning sessions. Individual cells exhibited prominent, bilateral coupling with fMRI fluctuations in a restricted set of cortical areas inside and outside the face patch network, partially matching the pattern of known anatomical projections. Within each face patch population, a subset of neurons was positively coupled with the face patch network and another was negatively coupled. The same cells showed inverse correlations with distinct subcortical structures, most notably the lateral geniculate nucleus and brainstem neuromodulatory centers. Corresponding connectivity maps derived from fMRI seeds and local field potentials differed from the single unit maps, particularly in subcortical areas. Together, the results demonstrate that the spiking fluctuations of neurons are selectively coupled with discrete brain regions, with the coupling governed in part by anatomical network connections and in part by indirect neuromodulatory pathways.
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Lee YJ, Bae H, Byun JC, Kwon S, Oh SS, Kim S. Clinical Usefulness of Simultaneous Electroencephalography and Functional Magnetic Resonance Imaging in Children With Focal Epilepsy. J Clin Neurol 2022; 18:535-546. [PMID: 36062771 PMCID: PMC9444567 DOI: 10.3988/jcn.2022.18.5.535] [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: 01/19/2022] [Revised: 04/04/2022] [Accepted: 04/04/2022] [Indexed: 11/17/2022] Open
Abstract
Background and Purpose The current study analyzed the interictal epileptiform discharge (IED)-related hemodynamic response and aimed to determine the clinical usefulness of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) in defining the epileptogenic zone (EZ) in children with focal epilepsy. Methods Patients with focal epilepsy showing IEDs on conventional EEG were evaluated using EEG-fMRI. Statistical analyses were performed using the times of spike as events modeled with multiple hemodynamic response functions. The area showing the most significant t-value for blood-oxygen-level-dependent (BOLD) changes was compared with the presumed EZ. Moreover, BOLD responses between -9 and +9 s around the spike times were analyzed to track the hemodynamic response patterns over time. Results Half (n=13) of 26 EEG-fMRI investigations of 19 patients were successful. Two patients showed 2 different types of spikes, resulting in 15 analyses. The maximum BOLD response was concordant with the EZ in 11 (73.3%) of the 15 analyses. In 10 (66.7%) analyses, the BOLD response localized the EZs more specifically. Focal BOLD responses in the EZs occurred before IEDs in 11 analyses and were often widespread after IEDs. Hemodynamic response patterns were consistent in the same epilepsy syndrome or when repeating the investigation in the same patients. Conclusions EEG-fMRI can provide additional information for localizing the EZ in children with focal epilepsy, and also reveal the pathogenesis of pediatric epilepsy by evaluating the patterns in the hemodynamic response across time windows of IEDs.
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Affiliation(s)
- Yun Jeong Lee
- Department of Pediatrics, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, Korea
| | - Hyunwoo Bae
- Department of Pediatrics, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, Korea
| | - Jun Chul Byun
- Department of Pediatrics, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, Daegu, Korea
| | - Soonhak Kwon
- Department of Pediatrics, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, Korea
| | - Sung Suk Oh
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI hub), Daegu, Korea.
| | - Saeyoon Kim
- Department of Pediatrics, Yeungnam University Medical Center, Yeungnam University College of Medicine, Daegu, Korea.
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Bernardes A, Couceiro R, Medeiros J, Henriques J, Teixeira C, Simões M, Durães J, Barbosa R, Madeira H, Carvalho P. How Reliable Are Ultra-Short-Term HRV Measurements during Cognitively Demanding Tasks? SENSORS (BASEL, SWITZERLAND) 2022; 22:6528. [PMID: 36080987 PMCID: PMC9460303 DOI: 10.3390/s22176528] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/24/2022] [Accepted: 08/24/2022] [Indexed: 06/15/2023]
Abstract
Ultra-short-term HRV features assess minor autonomous nervous system variations such as variations resulting from cognitive stress peaks during demanding tasks. Several studies compare ultra-short-term and short-term HRV measurements to investigate their reliability. However, existing experiments are conducted in low cognitively demanding environments. In this paper, we propose to evaluate these measurements' reliability under cognitively demanding tasks using a near real-life setting. For this purpose, we selected 31 HRV features, extracted from data collected from 21 programmers performing code comprehension, and compared them across 18 different time frames, ranging from 3 min to 10 s. Statistical significance and correlation tests were performed between the features extracted using the larger window (3 min) and the same features extracted with the other 17 time frames. We paired these analyses with Bland-Altman plots to inspect how the extraction window size affects the HRV features. The main results show 13 features that presented at least 50% correlation when using 60-second windows. The HF and mNN features achieved around 50% correlation using a 30-second window. The 30-second window was the smallest time frame considered to have reliable measurements. Furthermore, the mNN feature proved to be quite robust to the shortening of the time resolution.
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Kraljič A, Matkovič A, Purg N, Demšar J, Repovš G. Evaluation and comparison of most prevalent artifact reduction methods for EEG acquired simultaneously with fMRI. FRONTIERS IN NEUROIMAGING 2022; 1:968363. [PMID: 37555133 PMCID: PMC10406266 DOI: 10.3389/fnimg.2022.968363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/02/2022] [Indexed: 08/10/2023]
Abstract
Multimodal neuroimaging using EEG and fMRI provides deeper insights into brain function by improving the spatial and temporal resolution of the acquired data. However, simultaneous EEG-fMRI inevitably compromises the quality of the EEG and fMRI signals due to the high degree of interaction between the two systems. Fluctuations in the magnetic flux flowing through the participant and the EEG system, whether due to movement within the magnetic field of the scanner or to changes in magnetic field strength, induce electrical potentials in the EEG recordings that mask the much weaker electrical activity of the neuronal populations. A number of different methods have been proposed to reduce MR artifacts. We present an overview of the most commonly used methods and an evaluation of the methods using three sets of diverse EEG data. We limited the evaluation to open-access and easy-to-use methods and a reference signal regression method using a set of six carbon-wire loops (CWL), which allowed evaluation of their added value. The evaluation was performed by comparing EEG signals recorded outside the MRI scanner with artifact-corrected EEG signals recorded simultaneously with fMRI. To quantify and evaluate the quality of artifact reduction methods in terms of the spectral content of the signal, we analyzed changes in oscillatory activity during a resting-state and a finger tapping motor task. The quality of artifact reduction in the time domain was assessed using data collected during a visual stimulation task. In the study we utilized hierarchical Bayesian probabilistic modeling for statistical inference and observed significant differences between the evaluated methods in the success of artifact reduction and associated signal quality in both the frequency and time domains. In particular, the CWL system proved superior to the other methods evaluated in improving spectral contrast in the alpha and beta bands and in recovering visual evoked responses. Based on the results of the evaluation study, we proposed guidelines for selecting the optimal method for MR artifact reduction.
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Affiliation(s)
- Aleksij Kraljič
- Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
| | - Andraž Matkovič
- Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
| | - Nina Purg
- Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
| | - Jure Demšar
- Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
| | - Grega Repovš
- Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
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Li W, Zhang W, Jiang Z, Zhou T, Xu S, Zou L. Source localization and functional network analysis in emotion cognitive reappraisal with EEG-fMRI integration. Front Hum Neurosci 2022; 16:960784. [PMID: 36034109 PMCID: PMC9411793 DOI: 10.3389/fnhum.2022.960784] [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: 06/03/2022] [Accepted: 07/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background The neural activity and functional networks of emotion-based cognitive reappraisal have been widely investigated using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). However, single-mode neuroimaging techniques are limited in exploring the regulation process with high temporal and spatial resolution. Objectives We proposed a source localization method with multimodal integration of EEG and fMRI and tested it in the source-level functional network analysis of emotion cognitive reappraisal. Methods EEG and fMRI data were simultaneously recorded when 15 subjects were performing the emotional cognitive reappraisal task. Fused priori weighted minimum norm estimation (FWMNE) with sliding windows was proposed to trace the dynamics of EEG source activities, and the phase lag index (PLI) was used to construct the functional brain network associated with the process of downregulating negative affect using the reappraisal strategy. Results The functional networks were constructed with the measure of PLI, in which the important regions were indicated. In the gamma band source-level network analysis, the cuneus, the lateral orbitofrontal cortex, the superior parietal cortex, the postcentral gyrus, and the pars opercularis were identified as important regions in reappraisal with high betweenness centrality. Conclusion The proposed multimodal integration method for source localization identified the key cortices involved in emotion regulation, and the network analysis demonstrated the important brain regions involved in the cognitive control of reappraisal. It shows promise in the utility in the clinical setting for affective disorders.
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Affiliation(s)
- Wenjie Li
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, China
| | - Wei Zhang
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, China
| | - Zhongyi Jiang
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, China
| | - Tiantong Zhou
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, China
| | - Shoukun Xu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, China
| | - Ling Zou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, China
- Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou, China
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Zou G, Liu J, Zou Q, Gao JH. A-PASS: An automated pipeline to analyze simultaneously acquired EEG-fMRI data for studying brain activities during sleep. J Neural Eng 2022; 19. [PMID: 35878599 DOI: 10.1088/1741-2552/ac83f2] [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: 03/12/2022] [Accepted: 07/25/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Concurrent electroencephalography and functional magnetic resonance imaging (EEG-fMRI) signals can be used to uncover the nature of brain activities during sleep. However, analyzing simultaneously acquired EEG-fMRI data is extremely time consuming and experience dependent. Thus, we developed a pipeline, which we named A-PASS, to automatically analyze simultaneously acquired EEG-fMRI data for studying brain activities during sleep. APPROACH A deep learning model was trained on a sleep EEG-fMRI dataset from 45 subjects and used to perform sleep stage scoring. Various fMRI indices can be calculated with A-PASS to depict the neurophysiological characteristics across different sleep stages. We tested the performance of A-PASS on an independent sleep EEG-fMRI dataset from 28 subjects. Statistical maps regarding the main effect of sleep stages and differences between each pair of stages of fMRI indices were generated and compared using both A-PASS and manual processing methods. MAIN RESULTS The deep learning model implemented in A-PASS achieved both an accuracy and F1-score higher than 70% for sleep stage classification on EEG data acquired during fMRI scanning. The statistical maps generated from A-PASS largely resembled those produced from manually scored stages plus a combination of multiple software programs. SIGNIFICANCE A-PASS allowed efficient EEG-fMRI data processing without manual operation and could serve as a reliable and powerful tool for simultaneous EEG-fMRI studies on sleep.
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Affiliation(s)
- Guangyuan Zou
- Peking University, 5 Yiheyuan Road, Haidian District, Beijing, China, Beijing, 100871, CHINA
| | - Jiayi Liu
- Peking University, 5 Yiheyuan Road, Haidian District, Beijing, China, Beijing, 100871, CHINA
| | - Qihong Zou
- Peking University, 5 Yiheyuan Road, Haidian District, Beijing, China, Beijing, 100871, CHINA
| | - Jia-Hong Gao
- Peking University, 5 Yiheyuan Road, Haidian District, Beijing, China, Beijing, 100871, CHINA
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Cruttenden CE, Zhu W, Zhang Y, Zhu XH, Chen W, Rajamani R. Toward Completely Sampled Extracellular Neural Recording During fMRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:1735-1746. [PMID: 35120000 PMCID: PMC9634956 DOI: 10.1109/tmi.2022.3149002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
This work aims to estimate severe fMRI scanning artifacts in extracellular neural recordings made at ultrahigh magnetic field strengths in order to remove the artifact interferences and uncover the complete neural electrophysiology signal. We build on previous work that used PCA to denoise EEG recorded during fMRI, adapting it to cover the much larger frequency range (1-6000 Hz) of the extracellular field potentials (EFPs) observed by extracellular neural recordings. We examine the singular value decomposition (SVD)-PCA singular value shrinkage (SVS) and compare two shrinkage rules and a sliding template subtraction approach. Additionally, we present a new technique for estimating the singular value upper bounds in spontaneous neural activity recorded in the isoflurane anesthetized rat that uses the temporal first difference of the neural signal. The approaches are tested on artificial datasets to examine their efficacy in detecting extracellular action potentials (EAPs: 300-6000 Hz) recorded during fMRI gradient interferences. Our results indicate that it is possible to uncover the EAPs recorded during gradient interferences. The methods are then tested on natural (non-artificial) datasets recorded from the cortex of isoflurane anesthetized rats, where both local field potential (LFP: 1-300 Hz) and EAP signals are analyzed. The SVS methods are shown to be advantageous compared to sliding template subtraction, especially in the high frequency range corresponding to EAPs. Our novel approach moves us towards simultaneous fMRI and completely sampled neural recording (1-6000Hz with no temporal gaps), providing the opportunity for further study of spontaneous brain function and neurovascular coupling at ultrahigh field in the isoflurane anesthetized rat.
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Schwartz M, Yang B, Schick F. Classification-guided Neural Network-based Correction of Magnetic Resonance-related Gradient Artifact Residuals in Simultaneously Recorded Surface Electromyography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3632-3635. [PMID: 36085922 DOI: 10.1109/embc48229.2022.9871062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Spontaneous muscular activities can be studied by simultaneous recordings of surface electromyography (sEMG) and diffusion-weighted magnetic resonance imaging (DW-MRI). For reliable assessment of the spontaneous activity rate in sEMG data during active MR imaging, it is necessary to have a decent gradient artifact (GA) correction algorithm enabling the detection of small spontaneous activities with an amplitude of few microvolts. In this work, a neural network with weak label annotations during the training process is utilized for enhanced correction of GA residuals in the sEMG recordings. Based on sEMG signal decomposition and class-activation maps from the neural network classification, the amount of GA residuals is iteratively decreased in the sEMG signal. This leads to a reduction of the false-positive rate in automated spontaneous activity detection. Quality of GA residual correction is therefore estimated by using a specialized second neural network model. Clinical relevance- This work establishes an improved GA residual correction for simultaneously recorded sEMG data during MRI to enhance the ability for small spontaneous activity detection.
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Steinmann I, Williams KA, Wilke M, Antal A. Detection of Transcranial Alternating Current Stimulation Aftereffects Is Improved by Considering the Individual Electric Field Strength and Self-Rated Sleepiness. Front Neurosci 2022; 16:870758. [PMID: 35833087 PMCID: PMC9272587 DOI: 10.3389/fnins.2022.870758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Non-invasive electrical stimulation methods, such as transcranial alternating current stimulation (tACS), are increasingly used in human neuroscience research and offer potential new avenues to treat neurological and psychiatric disorders. However, their often variable effects have also raised concerns in the scientific and clinical communities. This study aims to investigate the influence of subject-specific factors on the alpha tACS-induced aftereffect on the alpha amplitude (measured with electroencephalography, EEG) as well as on the connectivity strength between nodes of the default mode network (DMN) [measured with functional magnetic resonance imaging (fMRI)]. As subject-specific factors we considered the individual electrical field (EFIELD) strength at target regions in the brain, the frequency mismatch between applied stimulation and individual alpha frequency (IAF) and as a covariate, subject’s changes in mental state, i.e., sleepiness. Eighteen subjects participated in a tACS and a sham session conducted on different days. Each session consisted of three runs (pre/stimulation/). tACS was applied during the second run at each subject’s individual alpha frequency (IAF), applying 1 mA peak-to-peak intensity for 7 min, using an occipital bihemispheric montage. In every run, subjects watched a video designed to increase in-scanner compliance. To investigate the aftereffect of tACS on EEG alpha amplitude and on DMN connectivity strength, EEG data were recorded simultaneously with fMRI data. Self-rated sleepiness was documented using a questionnaire. Conventional statistics (ANOVA) did not show a significant aftereffect of tACS on the alpha amplitude compared to sham stimulation. Including individual EFIELD strengths and self-rated sleepiness scores in a multiple linear regression model, significant tACS-induced aftereffects were observed. However, the subject-wise mismatch between tACS frequency and IAF had no contribution to our model. Neither standard nor extended statistical methods confirmed a tACS-induced aftereffect on DMN functional connectivity. Our results show that it is possible and necessary to disentangle alpha amplitude changes due to intrinsic mechanisms and to external manipulation using tACS on the alpha amplitude that might otherwise be overlooked. Our results suggest that EFIELD is really the most significant factor that explains the alpha amplitude modulation during a tACS session. This knowledge helps to understand the variability of the tACS-induced aftereffects.
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Affiliation(s)
- Iris Steinmann
- Department of Cognitive Neurology, University Medical Center Göttingen, Göttingen, Germany
- *Correspondence: Iris Steinmann,
| | - Kathleen A. Williams
- Department of Cognitive Neurology, University Medical Center Göttingen, Göttingen, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Melanie Wilke
- Department of Cognitive Neurology, University Medical Center Göttingen, Göttingen, Germany
- German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
| | - Andrea Antal
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
- Andrea Antal,
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Lee H, Graham SJ, Kuo W, Lin F. Ballistocardiogram suppression in concurrent EEG-MRI by dynamic modeling of heartbeats. Hum Brain Mapp 2022; 43:4444-4457. [PMID: 35695703 PMCID: PMC9435020 DOI: 10.1002/hbm.25965] [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: 01/04/2022] [Revised: 04/19/2022] [Accepted: 04/21/2022] [Indexed: 12/30/2022] Open
Abstract
The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work considering the variability of cardiac cycles and head motion across time and subjects is needed to provide highly robust correction. Here, a method called "dynamic modeling of heartbeats" (DMH) is proposed to reduce BCG artifacts in EEG data recorded inside an MRI system. The DMH method models BCG artifacts by combining EEG points at time instants with similar dynamics. The modeled BCG artifact is then subtracted from the EEG recording to suppress the BCG artifact. Performance of DMH was tested and specifically compared with the Optimal Basis Set (OBS) method on EEG data recorded inside a 3T MRI system with either no MRI acquisition (Inside-MRI), echo-planar imaging (EPI-EEG), or fast MRI acquisition using simultaneous multi-slice and inverse imaging methods (SMS-InI-EEG). In a steady-state visual evoked response (SSVEP) paradigm, the 15-Hz oscillatory neuronal activity at the visual cortex after DMH processing was about 130% of that achieved by OBS processing for Inside-MRI, SMS-InI-EEG, and EPI-EEG conditions. The DMH method is computationally efficient for suppressing BCG artifacts and in the future may help to improve the quality of EEG data recorded in high-field MRI systems for neuroscientific and clinical applications.
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Affiliation(s)
- Hsin‐Ju Lee
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada,Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Simon J. Graham
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada,Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Wen‐Jui Kuo
- Institute of NeuroscienceNational Yang Ming Chiao‐Tung UniversityTaipeiTaiwan,Brain Research CenterNational Yang‐Ming Chiao‐Tung UniversityTaipeiTaiwan
| | - Fa‐Hsuan Lin
- Physical Sciences PlatformSunnybrook Research InstituteTorontoOntarioCanada,Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
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Pfurtscheller G, Blinowska KJ, Kaminski M, Rassler B, Klimesch W. Processing of fMRI-related anxiety and information flow between brain and body revealed a preponderance of oscillations at 0.15/0.16 Hz. Sci Rep 2022; 12:9117. [PMID: 35650314 PMCID: PMC9160010 DOI: 10.1038/s41598-022-13229-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/23/2022] [Indexed: 11/09/2022] Open
Abstract
Slow oscillations of different center frequencies and their coupling play an important role in brain-body interactions. The crucial question analyzed by us is, whether the low frequency (LF) band (0.05-0.15 Hz) or the intermediate frequency (IMF) band (0.1-0.2 Hz) is more eminent in respect of the information flow between body (heart rate and respiration) and BOLD signals in cortex and brainstem. A recently published study with the LF band in fMRI-naïve subjects revealed an intensive information flow from the cortex to the brainstem and a weaker flow from the brainstem to the cortex. The comparison of both bands revealed a significant information flow from the middle frontal gyrus (MFG) to the precentral gyrus (PCG) and from brainstem to PCG only in the IMF band. This pattern of directed coupling between slow oscillations in the cortex and brainstem not only supports the existence of a pacemaker-like structure in brainstem, but provides first evidence that oscillations centered at 0.15/0.16 Hz can also emerge in brain networks. BOLD oscillations in resting states are dominating at ~ 0.08 Hz and respiratory rates at ~ 0.32 Hz. Therefore, the frequency component at ~ 0.16 Hz (doubling-halving 0.08 Hz or 0.32 Hz) is of special interest, because phase coupled oscillations can reduce the energy demand.
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Affiliation(s)
- Gert Pfurtscheller
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria.
| | - Katarzyna J Blinowska
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4 St., 02-109, Warsaw, Poland.,Faculty of Physics, University of Warsaw, Ul. Pasteura 5, 02-093, Warsaw, Poland
| | - Maciej Kaminski
- Faculty of Physics, University of Warsaw, Ul. Pasteura 5, 02-093, Warsaw, Poland
| | - Beate Rassler
- Carl-Ludwig-Institute of Physiology, University of Leipzig, Leipzig, Germany
| | - Wolfgang Klimesch
- Centre of Cognitive Neuroscience, University of Salzburg, Salzburg, Austria
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Samaha J, LaRocque JJ, Postle BR. Spontaneous alpha-band amplitude predicts subjective visibility but not discrimination accuracy during high-level perception. Conscious Cogn 2022; 102:103337. [PMID: 35525224 DOI: 10.1016/j.concog.2022.103337] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 02/17/2022] [Accepted: 04/26/2022] [Indexed: 11/30/2022]
Abstract
Near-threshold perception is a paradigm case of awareness diverging from reality - the perception of an unchanging stimulus can vacillate from undetected to clearly perceived. The amplitude of low-frequency brain oscillations - particularly in the alpha-band (8-13 Hz) - has emerged as a reliable predictor of trial-to-trial variability in perceptual decisions based on simple, low-level stimuli. Here, we addressed the question of how spontaneous oscillatory amplitude impacts subjective and objective aspects of perception using high-level visual stimuli. Human observers completed a near-threshold face/house discrimination task with subjective visibility ratings while electroencephalograms (EEG) were recorded. Using single-trial multiple regression analysis, we found that spontaneous fluctuations in prestimulus alpha-band amplitude were negatively related to visibility judgments but did not predict trial-by-trial accuracy. These results extend previous findings that indicate that strong prestimulus alpha diminishes subjective perception without affecting the accuracy or sensitivity (d') of perceptual decisions into the domain of high-level perception.
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Affiliation(s)
- Jason Samaha
- Department of Psychology, University of California, Santa Cruz, USA.
| | - Joshua J LaRocque
- Department of Neurology, New York University School of Medicine, USA
| | - Bradley R Postle
- Department of Psychiatry, University of Wisconsin-Madison, USA; Department of Psychology, University of Wisconsin-Madison, USA
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