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Zhang H, Zhou QQ, Chen H, Hu XQ, Li WG, Bai Y, Han JX, Wang Y, Liang ZH, Chen D, Cong FY, Yan JQ, Li XL. The applied principles of EEG analysis methods in neuroscience and clinical neurology. Mil Med Res 2023; 10:67. [PMID: 38115158 PMCID: PMC10729551 DOI: 10.1186/s40779-023-00502-7] [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: 10/25/2023] [Accepted: 11/23/2023] [Indexed: 12/21/2023] Open
Abstract
Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural signals, EEG has aroused much interest in scientific research and medical fields. This article reviews the types of EEG signals, multiple EEG signal analysis methods, and the application of relevant methods in the neuroscience field and for diagnosing neurological diseases. First, three types of EEG signals, including time-invariant EEG, accurate event-related EEG, and random event-related EEG, are introduced. Second, five main directions for the methods of EEG analysis, including power spectrum analysis, time-frequency analysis, connectivity analysis, source localization methods, and machine learning methods, are described in the main section, along with different sub-methods and effect evaluations for solving the same problem. Finally, the application scenarios of different EEG analysis methods are emphasized, and the advantages and disadvantages of similar methods are distinguished. This article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives, provide references for subsequent research, and summarize current issues and prospects for the future.
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Affiliation(s)
- Hao Zhang
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Qing-Qi Zhou
- College of Electrical and Control Engineering, North China University of Technology, Beijing, 100041, China
| | - He Chen
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China
| | - Xiao-Qing Hu
- Department of Psychology, the State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, 999077, China
- HKU-Shenzhen Institute of Research and Innovation, Shenzhen, 518057, Guangdong, China
| | - Wei-Guang Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, 999077, China
| | - Yang Bai
- Department of Rehabilitation Medicine, the First Affiliated Hospital of Nanchang University, Nanchang, 330006, China
- Rehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, 330006, China
| | - Jun-Xia Han
- Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, 100048, China
| | - Yao Wang
- School of Communication Science, Beijing Language and Culture University, Beijing, 100083, China
| | - Zhen-Hu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, Hebei, China.
| | - Dan Chen
- School of Computer Science, Wuhan University, Wuhan, 430072, China.
| | - Feng-Yu Cong
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116081, Liaoning, China.
| | - Jia-Qing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, 100041, China.
| | - Xiao-Li Li
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China.
- Guangdong Artificial Intelligence and Digital Economy Laboratory (Guangzhou), Guangzhou, 510335, China.
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González-García I, Visser M. A Semantic Cognition Contribution to Mood and Anxiety Disorder Pathophysiology. Healthcare (Basel) 2023; 11:healthcare11060821. [PMID: 36981478 PMCID: PMC10047953 DOI: 10.3390/healthcare11060821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/17/2023] [Accepted: 03/02/2023] [Indexed: 03/14/2023] Open
Abstract
Over the last two decades, the functional role of the bilateral anterior temporal lobes (bATLs) has been receiving more attention. They have been associated with semantics and social concept processing, and are regarded as a core region for depression. In the past, the role of the ATL has often been overlooked in semantic models based on functional magnetic resonance imaging (fMRI) due to geometric distortions in the BOLD signal. However, previous work has unequivocally associated the bATLs with these higher-order cognitive functions following advances in neuroimaging techniques to overcome the geometric distortions. At the same time, the importance of the neural basis of conceptual knowledge in understanding mood disorders became apparent. Theoretical models of the neural basis of mood and anxiety disorders have been classically studied from the emotion perspective, without concentrating on conceptual processing. However, recent work suggests that the ATL, a brain region underlying conceptual knowledge, plays an essential role in mood and anxiety disorders. Patients with anxiety and depression often cope with self-blaming biases and guilt. The theory is that in order to experience guilt, the brain needs to access the related conceptual information via the ATL. This narrative review describes how aberrant interactions of the ATL with the fronto–limbic emotional system could underlie mood and anxiety disorders.
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Bocharov AV, Savostyanov AN, Tamozhnikov SS, Karpova AG, Milakhina NS, Zavarzin EA, Saprigyn AE, Knyazev GG. Electrophysiological signatures of resting state networks under new environmental conditions. Neurosci Lett 2023; 794:137012. [PMID: 36521645 DOI: 10.1016/j.neulet.2022.137012] [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: 08/19/2022] [Revised: 11/29/2022] [Accepted: 12/08/2022] [Indexed: 12/14/2022]
Abstract
It is assumed that cognitive processes are provided by the regulatory interactions of different brain networks. The three most stable resting state networks, among which the default mode network (DMN), the central executive network (CEN) and the salience network (SN) are considered to be the key neurocognitive networks for understanding higher cognitive functions. Peculiarities of changes in the connectivity of resting state networks of an individual entering a new environment and after a year of adaptation in this environment remain poorly studied. The aim of this study was to investigate the peculiarities of the connectivity of resting state networks calculated in EEG data in students right after moving to an unfamiliar environment and one year after moving. 128-channel EEGs were recorded in the resting state in 45 students (all men) aged from 18 to 29 years, who moved to the North region of Russia (Yakutsk, Republic of Sakha (Yakutia)). Resting state networks were calculated by the seed-based method. The subjects had increased SN connectivity with the sensorimotor cortex and the posterior node of DMN (posterior cingulate cortex and precuneus) in the condition when they were exposed to a new unfamiliar environment, compared to the condition after a year in the same environment. In general, the obtained data are consistent with the notion of increased SN functioning when encountering new significant stimuli and tasks, i.e. new environmental conditions, and the representation of SN as closely related to the function of homeostasis regulation according to organism's internal goals and environmental requirements.
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Affiliation(s)
- Andrey V Bocharov
- Laboratory of Differential Psychophysiology, Scientific Research Institute of Neurosciences and Medicine, Novosibirsk 630117, Russia; Institute for the Humanities, Novosibirsk State University, Novosibirsk 630090, Russia.
| | - Alexander N Savostyanov
- Laboratory of Differential Psychophysiology, Scientific Research Institute of Neurosciences and Medicine, Novosibirsk 630117, Russia; Institute for the Humanities, Novosibirsk State University, Novosibirsk 630090, Russia; Laboratory of Psychological Genetics, Institute of Cytology and Genetics SB RAS, Novosibirsk 630090, Russia
| | - Sergey S Tamozhnikov
- Laboratory of Differential Psychophysiology, Scientific Research Institute of Neurosciences and Medicine, Novosibirsk 630117, Russia
| | | | - Natalya S Milakhina
- Laboratory of Psychological Genetics, Institute of Cytology and Genetics SB RAS, Novosibirsk 630090, Russia
| | - Evgeny A Zavarzin
- Laboratory of Differential Psychophysiology, Scientific Research Institute of Neurosciences and Medicine, Novosibirsk 630117, Russia
| | - Alexander E Saprigyn
- Laboratory of Differential Psychophysiology, Scientific Research Institute of Neurosciences and Medicine, Novosibirsk 630117, Russia; Laboratory of Psychological Genetics, Institute of Cytology and Genetics SB RAS, Novosibirsk 630090, Russia
| | - Gennady G Knyazev
- Laboratory of Differential Psychophysiology, Scientific Research Institute of Neurosciences and Medicine, Novosibirsk 630117, Russia
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4
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Duprez J, Tabbal J, Hassan M, Modolo J, Kabbara A, Mheich A, Drapier S, Vérin M, Sauleau P, Wendling F, Benquet P, Houvenaghel JF. Spatio-temporal dynamics of large-scale electrophysiological networks during cognitive action control in healthy controls and Parkinson's disease patients. Neuroimage 2022; 258:119331. [PMID: 35660459 DOI: 10.1016/j.neuroimage.2022.119331] [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: 12/13/2021] [Revised: 05/16/2022] [Accepted: 05/23/2022] [Indexed: 10/18/2022] Open
Abstract
Among the cognitive symptoms that are associated with Parkinson's disease (PD), alterations in cognitive action control (CAC) are commonly reported in patients. CAC enables the suppression of an automatic action, in favor of a goal-directed one. The implementation of CAC is time-resolved and arguably associated with dynamic changes in functional brain networks. However, the electrophysiological functional networks involved, their dynamic changes, and how these changes are affected by PD, still remain unknown. In this study, to address this gap of knowledge, 10 PD patients and 10 healthy controls (HC) underwent a Simon task while high-density electroencephalography (HD-EEG) was recorded. Source-level dynamic connectivity matrices were estimated using the phase-locking value in the beta (12-25 Hz) and gamma (30-45 Hz) frequency bands. Temporal independent component analyses were used as a dimension reduction tool to isolate the task-related brain network states. Typical microstate metrics were quantified to investigate the presence of these states at the subject-level. Our results first confirmed that PD patients experienced difficulties in inhibiting automatic responses during the task. At the group-level, we found three functional network states in the beta band that involved fronto-temporal, temporo-cingulate and fronto-frontal connections with typical CAC-related prefrontal and cingulate nodes (e.g., inferior frontal cortex). The presence of these networks did not differ between PD patients and HC when analyzing microstates metrics, and no robust correlations with behavior were found. In the gamma band, five networks were found, including one fronto-temporal network that was identical to the one found in the beta band. These networks also included CAC-related nodes previously identified in different neuroimaging modalities. Similarly to the beta networks, no subject-level differences were found between PD patients and HC. Interestingly, in both frequency bands, the dominant network at the subject-level was never the one that was the most durably modulated by the task. Altogether, this study identified the dynamic functional brain networks observed during CAC, but did not highlight PD-related changes in these networks that might explain behavioral changes. Although other new methods might be needed to investigate the presence of task-related networks at the subject-level, this study still highlights that task-based dynamic functional connectivity is a promising approach in understanding the cognitive dysfunctions observed in PD and beyond.
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Key Words
- Cognitive control
- DIFFIT, Difference in data fitting
- DLPFC, Dorso-lateral prefrontal cortex
- EEG, Electroencephalography
- FC, Functional connectivity
- Functional connectivity
- HC, Healthy controls
- HD-EEG, High-density EEG
- ICA, Independent component analysis
- IFC, Inferior frontal cortex
- MEG, Magnetoencephalography
- Networks, Dynamics
- PD, Parkinson's disease
- PLV, Phase locking value
- Parkinson's disease Abbreviations CAC, Cognitive action control
- ROIS, Regions of interest
- RT, Reaction time
- Simon task
- dBNS, Dynamic brain network state
- dFC, Dynamic functional connectivity
- fMRI, Functional magnetic resonance imaging
- high density EEG
- pre-SMA, Pre-supplementary motor area
- tICA, Temporal ICA
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Affiliation(s)
- Joan Duprez
- Univ Rennes, LTSI - U1099, F-35000 Rennes, France
| | - Judie Tabbal
- Univ Rennes, LTSI - U1099, F-35000 Rennes, France; Azm Center for Research in Biotechnology and Its Applications, EDST, Lebanese University, Beirut, Lebanon
| | - Mahmoud Hassan
- MINDig, F-35000 Rennes, France; School of Engineering, Reykjavik University, Iceland
| | | | | | | | - Sophie Drapier
- CIC INSERM 1414, Rennes, France; Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France
| | - Marc Vérin
- Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France; Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France
| | - Paul Sauleau
- Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France; Neurophysiology department, Rennes University Hospital, France
| | | | | | - Jean-François Houvenaghel
- Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France; Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France
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5
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Li J, Liu J, Zhong Y, Wang H, Yan B, Zheng K, Wei L, Lu H, Li B. Causal Interactions Between the Default Mode Network and Central Executive Network in Patients with Major Depression. Neuroscience 2021; 475:93-102. [PMID: 34487819 DOI: 10.1016/j.neuroscience.2021.08.033] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 08/25/2021] [Accepted: 08/26/2021] [Indexed: 11/15/2022]
Abstract
Two different but interacting neural systems exist in the human brain: the task positive networks and task negative networks. One of the most important task positive networks is the central executive network (CEN), while the task negative network generally refers to the default mode network (DMN), which usually demonstrates task-induced deactivation. Although previous studies have clearly shown the association of both the CEN and DMN with major depressive disorder (MDD), how the causal interactions between these two networks change in depressed patients remains unclear. In the current study, 99 subjects (43 patients with MDD and 56 healthy controls) were recruited with their resting-state fMRI data collected. After data preprocessing, spectral dynamic causal modeling (spDCM) was used to investigate the causal interactions within and between the DMN and CEN. Group commonalities and differences in causal interaction patterns within and between the CEN and DMN in patients and controls were assessed by a parametric empirical Bayes (PEB) model. Both subject groups demonstrated significant effective connectivity between regions of the CEN and DMN. In particular, we detected inhibitory influences from the CEN to the DMN with node-level PEB analyses, which may help to explain the anticorrelations between these two networks consistently reported in previous studies. Compared with healthy controls, patients with MDD showed increased effective connectivity within the CEN and decreased connectivity from regions of the CEN to DMN, suggesting impaired control of the DMN by the CEN in these patients. These findings might provide new insights into the neural substrates of MDD.
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Affiliation(s)
- Jiaming Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China; School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Jian Liu
- Network Center, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Yufang Zhong
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Huaning Wang
- Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Baoyu Yan
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Kaizhong Zheng
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Lei Wei
- Network Center, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Hongbing Lu
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
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6
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Maallo AMS, Moulton EA, Sieberg CB, Giddon DB, Borsook D, Holmes SA. A lateralized model of the pain-depression dyad. Neurosci Biobehav Rev 2021; 127:876-883. [PMID: 34090918 PMCID: PMC8289740 DOI: 10.1016/j.neubiorev.2021.06.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 06/01/2021] [Indexed: 11/25/2022]
Abstract
Chronic pain and depression are two frequently co-occurring and debilitating conditions. Even though the former is treated as a physical affliction, and the latter as a mental illness, both disorders closely share neural substrates. Here, we review the association of pain with depression, especially when symptoms are lateralized on either side of the body. We also explore the overlapping regions in the forebrain implicated in these conditions. Finally, we synthesize these findings into a model, which addresses gaps in our understanding of comorbid pain and depression. Our lateralized pain-depression dyad model suggests that individuals diagnosed with depression should be closely monitored for pain symptoms in the left hemibody. Conversely, for patients in pain, with the exception of acute pain with a known source, referrals in today's pain centers for psychological evaluation should be part of standard practice, within the framework of an interdisciplinary approach to pain treatment.
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Affiliation(s)
- Anne Margarette S Maallo
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Eric A Moulton
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christine B Sieberg
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Biobehavioral Pediatric Pain Lab, Department of Psychiatry & Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Donald B Giddon
- Harvard School of Dental Medicine, Harvard University, Boston, MA, USA; Pain Management Center, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - David Borsook
- Harvard Medical School, Boston, MA, USA; Departments of Psychiatry and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Scott A Holmes
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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Knyazev GG, Savostyanov AN, Bocharov AV, Rudych PD. How Self-Appraisal Is Mediated by the Brain. Front Hum Neurosci 2021; 15:700046. [PMID: 34267632 PMCID: PMC8275999 DOI: 10.3389/fnhum.2021.700046] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 06/03/2021] [Indexed: 12/28/2022] Open
Abstract
Self-appraisal is a process that leads to the formation of self-esteem, which contributes to subjective well-being and mental health. Neuroimaging studies link self-esteem with the activity of the medial prefrontal cortex (MPFC), right temporoparietal junction (rTPJ), posterior cingulate cortex (PCC), anterior insula (AIns), and dorsolateral prefrontal cortex. It is not known, however, how the process of self-appraisal itself is mediated by the brain and how different nodes of the self-appraisal network interact with each other. In this study, we used multilevel mediation analysis of functional MRI data recorded during the trait adjective judgment task, treating the emotional valence of adjectives as the predictor, behavioral response as the dependent variable, and brain activity as the mediator. The mediation effect was revealed in the rTPJ. Dynamic causal modeling showed that positive self-descriptions trigger communication within the network, with the rTPJ exerting the strongest excitatory output and MPFC receiving the strongest excitatory input. rAIns receives the strongest inhibitory input and sends exclusively inhibitory connections to other regions pointing out to its role in the processing of negative self-descriptions. Analysis of individual differences showed that in some individuals, self-appraisal is mostly driven by the endorsement of positive self-descriptions and is accompanied by increased activation and communication between rTPJ, MPFC, and PCC. In others, self-appraisal is driven by the rejection of negative self-descriptions and is accompanied by increased activation of rAIns and inhibition of PCC and MPFC. Membership of these groups was predicted by different personality variables. This evidence uncovers different mechanisms of positive self-bias, which may contribute to different facets of self-esteem and are associated with different personality profiles.
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Affiliation(s)
- Gennady G Knyazev
- Laboratory of Psychophysiology of Individual Differences, Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine, Novosibirsk, Russia
| | - Alexander N Savostyanov
- Laboratory of Psychophysiology of Individual Differences, Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine, Novosibirsk, Russia.,Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia.,Laboratory of Psychological Genetics at the Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Andrey V Bocharov
- Laboratory of Psychophysiology of Individual Differences, Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine, Novosibirsk, Russia.,Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Pavel D Rudych
- Laboratory of Psychophysiology of Individual Differences, Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine, Novosibirsk, Russia
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8
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Leicht G, Björklund J, Vauth S, Mußmann M, Haaf M, Steinmann S, Rauh J, Mulert C. Gamma-band synchronisation in a frontotemporal auditory information processing network. Neuroimage 2021; 239:118307. [PMID: 34174389 DOI: 10.1016/j.neuroimage.2021.118307] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 05/25/2021] [Accepted: 06/23/2021] [Indexed: 01/22/2023] Open
Abstract
Neural oscillations are fundamental mechanisms of the human brain that enable coordinated activity of different brain regions during perceptual and cognitive processes. A frontotemporal network generated by means of gamma oscillations and comprising the auditory cortex (AC) and the anterior cingulate cortex (ACC) has been shown to be involved in the cognitively demanding auditory information processing. This study aims to reveal patterns of functional and effective connectivity within this network in healthy subjects by means of simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We simultaneously recorded EEG and fMRI in 28 healthy subjects during the performance of a cognitively demanding auditory choice reaction task. Connectivity between the ACC and AC was analysed employing EEG and fMRI connectivity measures. We found a significant BOLD signal correlation between the ACC and AC, a significant task-dependant increase of fMRI connectivity (gPPI) and a significant increase in functional coupling in the gamma frequency range between these regions (LPS), which was increased in top-down direction (granger analysis). EEG and fMRI connectivity measures were positively correlated. The results of these study point to a role of a top-down influence of the ACC on the AC executed by means of gamma synchronisation. The replication of fMRI connectivity patterns in simultaneously recorded EEG data and the correlation between connectivity measures from both domains found in our study show, that brain connectivity based on the synchronisation of gamma oscillations is mirrored in fMRI connectivity patterns.
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Affiliation(s)
- Gregor Leicht
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany.
| | - Jonas Björklund
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany
| | - Sebastian Vauth
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany
| | - Marius Mußmann
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany
| | - Moritz Haaf
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany
| | - Saskia Steinmann
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany
| | - Jonas Rauh
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany
| | - Christoph Mulert
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany; Center of Psychiatry, Justus-Liebig University, Giessen, Germany
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9
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Martens M, Filippini N, Masaki C, Godlewska BR. Functional Connectivity between Task-Positive Networks and the Left Precuneus as a Biomarker of Response to Lamotrigine in Bipolar Depression: A Pilot Study. Pharmaceuticals (Basel) 2021; 14:534. [PMID: 34204977 PMCID: PMC8229811 DOI: 10.3390/ph14060534] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/23/2021] [Accepted: 05/28/2021] [Indexed: 12/12/2022] Open
Abstract
Treatment of bipolar depression poses a significant clinical challenge. Lamotrigine is one of a few efficacious drugs, however, it needs to be titrated very slowly and response can only be assessed after 10-12 weeks. With only a proportion of patients responding, an exploration of factors underlying treatment responsivity is of paramount clinical importance, as it may lead to an allocation of the drug to those most likely to respond to it. This study aimed at identifying differences in patterns of pre-treatment resting state functional connectivity (rsFC) that may underlie response to lamotrigine in bipolar depression. After a baseline MRI scan, twenty-one patients with bipolar depression were treated with lamotrigine in an open-label design; response, defined as ≥50% decrease in Hamilton Depression Rating Scale (HAMD) score, was assessed after 10-12 weeks of treatment. Twenty healthy controls had a baseline clinical assessment and scan but did not receive any treatment. Fifteen out of 21 (71%) patients responded to lamotrigine. Treatment responsivity was associated with enhanced pre-treatment rsFC of the right fronto-parietal network (FPN) and dorsal attention network (DAN) with left precuneus. The lack of treatment response was additionally characterised by reduced rsFC: of the DAN with right middle temporal gyrus; of the default mode network (DMN) with left precuneus; of the extended sensory-motor area with areas including the left hippocampus/left amygdala and left subcallosal cortex/nucleus accumbens; and of the left FPN with left inferior temporal gyrus/occipital fusiform gyrus/lateral occipital cortex. The results suggest that preserved rsFC between the FPN and DAN, the networks involved in cognitive control, and the hub of the posterior DMN, the left precuneus, may be critical for good response to lamotrigine as an add-on treatment in patients with bipolar depression. The study also suggests a more general decrease in rsFC to be related to poor treatment responsivity.
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Affiliation(s)
- Marieke Martens
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (M.M.); (C.M.)
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK;
| | - Nicola Filippini
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK;
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Charles Masaki
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (M.M.); (C.M.)
| | - Beata R. Godlewska
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (M.M.); (C.M.)
- Oxford Health NHS Foundation Trust, Oxford OX3 7JX, UK
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10
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Brain Networks Connectivity in Mild to Moderate Depression: Resting State fMRI Study with Implications to Nonpharmacological Treatment. Neural Plast 2021; 2021:8846097. [PMID: 33510782 PMCID: PMC7822653 DOI: 10.1155/2021/8846097] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 12/04/2020] [Accepted: 12/21/2020] [Indexed: 12/27/2022] Open
Abstract
Network mechanisms of depression development and especially of improvement from nonpharmacological treatment remain understudied. The current study is aimed at examining brain networks functional connectivity in depressed patients and its dynamics in nonpharmacological treatment. Resting state fMRI data of 21 healthy adults and 51 patients with mild or moderate depression were analyzed with spatial independent component analysis; then, correlations between time series of the components were calculated and compared between-group (study 1). Baseline and repeated-measure data of 14 treated (psychotherapy or fMRI neurofeedback) and 15 untreated depressed participants were similarly analyzed and correlated with changes in depression scores (study 2). Aside from diverse findings, studies 1 and 2 both revealed changes in within-default mode network (DMN) and DMN to executive control network (ECN) connections. Connectivity in one pair, initially lower in depression, decreased in no treatment group and was inversely correlated with Montgomery-Asberg depression score change in treatment group. Weak baseline connectivity in this pair also predicted improvement on Montgomery-Asberg scale in both treatment and no treatment groups. Coupling of another pair, initially stronger in depression, increased in therapy though was unrelated to improvement. The results demonstrate possible role of within-DMN and DMN-ECN functional connectivity in depression treatment and suggest that neural mechanisms of nonpharmacological treatment action may be unrelated to normalization of initially disrupted connectivity.
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Knyazev GG, Savostyanov AN, Bocharov AV, Levin EA, Rudych PD. Intrinsic Connectivity Networks in the Self- and Other-Referential Processing. Front Hum Neurosci 2020; 14:579703. [PMID: 33304255 PMCID: PMC7693553 DOI: 10.3389/fnhum.2020.579703] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 10/05/2020] [Indexed: 12/26/2022] Open
Abstract
Neuroimaging studies have revealed a multitude of brain regions associated with self- and other-referential processing, but the question how the distinction between self, close other, and distant other is processed in the brain still remains unanswered. The default mode network (DMN) is the primary network associated with the processing of self, whereas task-positive networks (TPN) are indispensable for the processing of external objects. We hypothesize that self- and close-other-processing would engage DMN more than TPN, whereas distant-other-processing would engage TPN to a greater extent. To test this hypothesis, we used functional magnetic resonance imaging (fMRI) functional connectivity data obtained in the course of a trait adjective judgment task while subjects evaluated themselves, the best friend, a neutral stranger, and an unpleasant person. A positive association between the degree of self-relatedness and the degree of DMN dominance was revealed in cortical midline structures (CMS) and the left lateral prefrontal cortex. Relative to TPN, DMN showed greater connectivity in me than in friend, in friend than in stranger, and in stranger than in unpleasant conditions. These results show that the less the evaluated person is perceived as self-related, the more the balance of activity in the brain shifts from the DMN to the TPN.
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Affiliation(s)
- Gennady G Knyazev
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Alexander N Savostyanov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia.,Joint Laboratory of Psychological Genetics at the Institute of Cytology and Genetics SB RAS, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Andrey V Bocharov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Evgeny A Levin
- E.N. Meshalkin National Medical Research Center, Novosibirsk, Russia
| | - Pavel D Rudych
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
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12
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Alonso Martínez S, Deco G, Ter Horst GJ, Cabral J. The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample. Front Neural Circuits 2020; 14:570583. [PMID: 33071760 PMCID: PMC7530893 DOI: 10.3389/fncir.2020.570583] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 08/26/2020] [Indexed: 12/17/2022] Open
Abstract
Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.
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Affiliation(s)
- Sonsoles Alonso Martínez
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Gert J Ter Horst
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Joana Cabral
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Center for Music in the Brain, Aarhus University, Aarhus, Denmark.,Life and Health Sciences Research Institute (ICVS), University of Minho, Minho, Portugal
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13
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Frewen P, Schroeter ML, Riva G, Cipresso P, Fairfield B, Padulo C, Kemp AH, Palaniyappan L, Owolabi M, Kusi-Mensah K, Polyakova M, Fehertoi N, D’Andrea W, Lowe L, Northoff G. Neuroimaging the consciousness of self: Review, and conceptual-methodological framework. Neurosci Biobehav Rev 2020; 112:164-212. [DOI: 10.1016/j.neubiorev.2020.01.023] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Revised: 01/06/2020] [Accepted: 01/20/2020] [Indexed: 01/04/2023]
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14
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Arias JA, Williams C, Raghvani R, Aghajani M, Baez S, Belzung C, Booij L, Busatto G, Chiarella J, Fu CH, Ibanez A, Liddell BJ, Lowe L, Penninx BWJH, Rosa P, Kemp AH. The neuroscience of sadness: A multidisciplinary synthesis and collaborative review. Neurosci Biobehav Rev 2020; 111:199-228. [PMID: 32001274 DOI: 10.1016/j.neubiorev.2020.01.006] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 12/17/2019] [Accepted: 01/05/2020] [Indexed: 02/06/2023]
Abstract
Sadness is typically characterized by raised inner eyebrows, lowered corners of the mouth, reduced walking speed, and slumped posture. Ancient subcortical circuitry provides a neuroanatomical foundation, extending from dorsal periaqueductal grey to subgenual anterior cingulate, the latter of which is now a treatment target in disorders of sadness. Electrophysiological studies further emphasize a role for reduced left relative to right frontal asymmetry in sadness, underpinning interest in the transcranial stimulation of left dorsolateral prefrontal cortex as an antidepressant target. Neuroimaging studies - including meta-analyses - indicate that sadness is associated with reduced cortical activation, which may contribute to reduced parasympathetic inhibitory control over medullary cardioacceleratory circuits. Reduced cardiac control may - in part - contribute to epidemiological reports of reduced life expectancy in affective disorders, effects equivalent to heavy smoking. We suggest that the field may be moving toward a theoretical consensus, in which different models relating to basic emotion theory and psychological constructionism may be considered as complementary, working at different levels of the phylogenetic hierarchy.
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Affiliation(s)
- Juan A Arias
- Department of Psychology, Swansea University, United Kingdom; Department of Statistics, Mathematical Analysis, and Operational Research, Universidade de Santiago de Compostela, Spain
| | - Claire Williams
- Department of Psychology, Swansea University, United Kingdom
| | - Rashmi Raghvani
- Department of Psychology, Swansea University, United Kingdom
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location VUMC, GGZ InGeest Research & Innovation, Amsterdam Neuroscience, the Netherlands
| | | | | | - Linda Booij
- Department of Psychology, Concordia University Montreal, Canada; CHU Sainte-Justine, University of Montreal, Montreal, Canada
| | | | - Julian Chiarella
- Department of Psychology, Concordia University Montreal, Canada; CHU Sainte-Justine, University of Montreal, Montreal, Canada
| | - Cynthia Hy Fu
- School of Psychology, University of East London, United Kingdom; Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Agustin Ibanez
- Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile; Universidad Autonoma del Caribe, Barranquilla, Colombia; Centre of Excellence in Cognition and its Disorders, Australian Research Council (ARC), New South Wales, Australia
| | | | - Leroy Lowe
- Neuroqualia (NGO), Turo, Nova Scotia, Canada
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam UMC, Location VUMC, GGZ InGeest Research & Innovation, Amsterdam Neuroscience, the Netherlands
| | - Pedro Rosa
- Department of Psychiatry, University of Sao Paulo, Brazil
| | - Andrew H Kemp
- Department of Psychology, Swansea University, United Kingdom; Department of Psychiatry, University of Sao Paulo, Brazil; Discipline of Psychiatry, and School of Psychology, University of Sydney, Sydney, Australia.
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15
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Coquelet N, De Tiège X, Destoky F, Roshchupkina L, Bourguignon M, Goldman S, Peigneux P, Wens V. Comparing MEG and high-density EEG for intrinsic functional connectivity mapping. Neuroimage 2020; 210:116556. [DOI: 10.1016/j.neuroimage.2020.116556] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 12/11/2019] [Accepted: 01/14/2020] [Indexed: 01/22/2023] Open
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16
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Wens V, Bourguignon M, Vander Ghinst M, Mary A, Marty B, Coquelet N, Naeije G, Peigneux P, Goldman S, De Tiège X. Synchrony, metastability, dynamic integration, and competition in the spontaneous functional connectivity of the human brain. Neuroimage 2019; 199:313-324. [PMID: 31170458 DOI: 10.1016/j.neuroimage.2019.05.081] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 04/25/2019] [Accepted: 05/29/2019] [Indexed: 11/25/2022] Open
Abstract
The human brain is functionally organized into large-scale neural networks that are dynamically interconnected. Multiple short-lived states of resting-state functional connectivity (rsFC) identified transiently synchronized networks and cross-network integration. However, little is known about the way brain couplings covary as rsFC states wax and wane. In this magnetoencephalography study, we explore the synchronization structure among the spontaneous interactions of well-known resting-state networks (RSNs). To do so, we extracted modes of dynamic coupling that reflect rsFC synchrony and analyzed their spatio-temporal features. These modes identified transient, sporadic rsFC changes characterized by the widespread integration of RSNs across the brain, most prominently in the β band. This is in line with the metastable rsFC state model of resting-state dynamics, wherein our modes fit as state transition processes. Furthermore, the default-mode network (DMN) stood out as being structured into competitive cross-network couplings with widespread DMN-RSN interactions, especially among the β-band modes. These results substantiate the theory that the DMN is a core network enabling dynamic global brain integration in the β band.
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Affiliation(s)
- Vincent Wens
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium; Magnetoencephalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB - Hôpital Erasme, Brussels, Belgium.
| | - Mathieu Bourguignon
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium; Laboratoire Cognition Langage et Développement, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium; BCBL - Basque Center on Cognition, Brain and Language, 20009 San Sebastian, Spain
| | - Marc Vander Ghinst
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Alison Mary
- UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Brice Marty
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Nicolas Coquelet
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Gilles Naeije
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Philippe Peigneux
- UR2NF - Neuropsychology and Functional Neuroimaging Research Unit at CRCN - Centre de Recherches Cognition et Neurosciences, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Serge Goldman
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium; Magnetoencephalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB - Hôpital Erasme, Brussels, Belgium
| | - Xavier De Tiège
- LCFC - Laboratoire de Cartographie fonctionnelle du Cerveau, UNI - ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium; Magnetoencephalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB - Hôpital Erasme, Brussels, Belgium
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Figueroa CA, Cabral J, Mocking RJT, Rapuano KM, van Hartevelt TJ, Deco G, Expert P, Schene AH, Kringelbach ML, Ruhé HG. Altered ability to access a clinically relevant control network in patients remitted from major depressive disorder. Hum Brain Mapp 2019; 40:2771-2786. [PMID: 30864248 PMCID: PMC6865599 DOI: 10.1002/hbm.24559] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2018] [Revised: 01/30/2019] [Accepted: 02/21/2019] [Indexed: 01/01/2023] Open
Abstract
Neurobiological models to explain vulnerability of major depressive disorder (MDD) are scarce and previous functional magnetic resonance imaging studies mostly examined “static” functional connectivity (FC). Knowing that FC constantly evolves over time, it becomes important to assess how FC dynamically differs in remitted‐MDD patients vulnerable for new depressive episodes. Using a recently developed method to examine dynamic FC, we characterized re‐emerging FC states during rest in 51 antidepressant‐free MDD patients at high risk of recurrence (≥2 previous episodes), and 35 healthy controls. We examined differences in occurrence, duration, and switching profiles of FC states after neutral and sad mood induction. Remitted MDD patients showed a decreased probability of an FC state (p < 0.005) consisting of an extensive network connecting frontal areas—important for cognitive control—with default mode network, striatum, and salience areas, involved in emotional and self‐referential processing. Even when this FC state was observed in patients, it lasted shorter (p < 0.005) and was less likely to switch to a smaller prefrontal–striatum network (p < 0.005). Differences between patients and controls decreased after sad mood induction. Further, the duration of this FC state increased in remitted patients after sad mood induction but not in controls (p < 0.05). Our findings suggest reduced ability of remitted‐MDD patients, in neutral mood, to access a clinically relevant control network involved in the interplay between externally and internally oriented attention. When recovering from sad mood, remitted recurrent MDD appears to employ a compensatory mechanism to access this FC state. This study provides a novel neurobiological profile of MDD vulnerability.
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Affiliation(s)
- Caroline A Figueroa
- Department of Psychiatry, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Brain Imaging Center, Academic Medical Center, Amsterdam, The Netherlands.,School of Social Welfare, University of California Berkeley, Berkeley, California
| | - Joana Cabral
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.,Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Roel J T Mocking
- Department of Psychiatry, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Brain Imaging Center, Academic Medical Center, Amsterdam, The Netherlands
| | - Kristina M Rapuano
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire
| | | | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Paul Expert
- Centre for Mathematics of Precision Healthcare, Imperial College London, London, United Kingdom.,Department of Mathematics, Imperial College London, London, United Kingdom
| | - Aart H Schene
- Department of Psychiatry, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.,Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Henricus G Ruhé
- Department of Psychiatry, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
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18
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O'Neill GC, Tewarie P, Vidaurre D, Liuzzi L, Woolrich MW, Brookes MJ. Dynamics of large-scale electrophysiological networks: A technical review. Neuroimage 2018; 180:559-576. [PMID: 28988134 DOI: 10.1016/j.neuroimage.2017.10.003] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 09/23/2017] [Accepted: 10/02/2017] [Indexed: 12/12/2022] Open
Abstract
For several years it has been argued that neural synchronisation is crucial for cognition. The idea that synchronised temporal patterns between different neural groups carries information above and beyond the isolated activity of these groups has inspired a shift in focus in the field of functional neuroimaging. Specifically, investigation into the activation elicited within certain regions by some stimulus or task has, in part, given way to analysis of patterns of co-activation or functional connectivity between distal regions. Recently, the functional connectivity community has been looking beyond the assumptions of stationarity that earlier work was based on, and has introduced methods to incorporate temporal dynamics into the analysis of connectivity. In particular, non-invasive electrophysiological data (magnetoencephalography/electroencephalography (MEG/EEG)), which provides direct measurement of whole-brain activity and rich temporal information, offers an exceptional window into such (potentially fast) brain dynamics. In this review, we discuss challenges, solutions, and a collection of analysis tools that have been developed in recent years to facilitate the investigation of dynamic functional connectivity using these imaging modalities. Further, we discuss the applications of these approaches in the study of cognition and neuropsychiatric disorders. Finally, we review some existing developments that, by using realistic computational models, pursue a deeper understanding of the underlying causes of non-stationary connectivity.
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Affiliation(s)
- George C O'Neill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Prejaas Tewarie
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Diego Vidaurre
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Lucrezia Liuzzi
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
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Knyazev GG, Merkulova EA, Savostyanov AN, Bocharov AV, Saprigyn AE. Effect of Cultural Priming on Social Behavior and EEG Correlates of Self-Processing. Front Behav Neurosci 2018; 12:236. [PMID: 30349465 PMCID: PMC6186948 DOI: 10.3389/fnbeh.2018.00236] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 09/21/2018] [Indexed: 11/30/2022] Open
Abstract
Humans are social beings and the self is inevitably conceptualized in terms of social environment. The degree to which the self is perceived as fundamentally similar or fundamentally different from other people is modulated by cultural stereotypes, such as collectivism and individualism. These stereotypes are not hardwired in our brains and individuals differ in the degree to which they adopt the attitudes that define their culture. Moreover, individuals can acquire multiple sets of cultural knowledge and, depending on the context, either individualistic or collectivistic cultural mindset could be activated. In this study, we used cultural priming techniques to activate either individualistic or collectivistic mindset and investigated the association between source-level EEG connectivity in the default mode network (DMN) and spontaneous self-related thoughts in the subsequent resting state. Afterward, participants performed a social interaction task, in which they were allowed to choose between friendly, avoidant, or aggressive behavior. After collectivism priming, self-related thoughts were associated with increased connectivity of DMN with the right temporoparietal junction (TPJ), which is involved in taking the perspective of others and is more active in representatives of collectivistic cultures, whereas after individualism priming they were associated with increased connectivity with the temporal pole, which is involved in self/other discrimination and is more active in representatives of individualistic cultures. Individual differences in the intensity of post-priming self-related thoughts and the strength of DMN-temporal pole connectivity predicted individual differences in behavior during the social interaction task, with individualistic mindset predisposing to more friendly and trustful social behavior.
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Affiliation(s)
- Gennady G. Knyazev
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Ekaterina A. Merkulova
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Alexander N. Savostyanov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
- Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Andrey V. Bocharov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
- Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Alexander E. Saprigyn
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
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20
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Knyazev GG, Savostyanov AN, Bocharov AV, Brak IV, Osipov EA, Filimonova EA, Saprigyn AE, Aftanas LI. Task-positive and task-negative networks in major depressive disorder: A combined fMRI and EEG study. J Affect Disord 2018; 235:211-219. [PMID: 29656269 DOI: 10.1016/j.jad.2018.04.003] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 02/23/2018] [Accepted: 04/02/2018] [Indexed: 10/17/2022]
Abstract
BACKGROUND The study of intrinsic connectivity networks, i.e., sets of brain regions that show a high degree of interconnectedness even in the absence of a task, showed that major depressive disorder (MDD) patients demonstrate an increased connectivity within the default mode network (DMN), which is active in a resting state and is implicated in self-referential processing, and a decreased connectivity in task-positive networks (TPNs), which increase their activity in attention tasks. Cortical localization of this 'dominance' of the DMN over the TPN in MDD patients is not fully understood. Besides, this effect has been investigated using fMRI and its electrophysiological underpinning is not known. METHOD In this study, we tested the dominance hypothesis using seed-based connectivity analysis of resting-state fMRI and EEG data obtained in 41 MDD patients and 23 controls. RESULTS In MDD patients, as compared to controls, insula, pallidum/putamen, amygdala, and left dorso- and ventrolateral prefrontal cortex are more strongly connected with DMN than with TPN seeds. In EEG, all significant effects were obtained in the delta frequency band. LIMITATIONS fMRI and EEG data were not obtained simultaneously during the same session. CONCLUSIONS In MDD patients, major emotion and attention regulation circuits are more strongly connected with DMN than with TPN implying they are more prepared to respond to internally generated self-related thoughts than to environmental challenges.
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Affiliation(s)
- Gennady G Knyazev
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia.
| | - Alexander N Savostyanov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia; Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Andrey V Bocharov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia; Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Ivan V Brak
- Laboratory of Affective and Cognitive Neuroscience, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Evgeny A Osipov
- Laboratory of Affective and Cognitive Neuroscience, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Elena A Filimonova
- Laboratory of Affective and Cognitive Neuroscience, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Alexander E Saprigyn
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Lyubomir I Aftanas
- Laboratory of Affective and Cognitive Neuroscience, Institute of Physiology and Basic Medicine, Novosibirsk, Russia; Department of Neuroscience, Novosibirsk State University, Novosibirsk, Russia
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Li C, Yuan H, Shou G, Cha YH, Sunderam S, Besio W, Ding L. Cortical Statistical Correlation Tomography of EEG Resting State Networks. Front Neurosci 2018; 12:365. [PMID: 29899686 PMCID: PMC5988892 DOI: 10.3389/fnins.2018.00365] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Accepted: 05/11/2018] [Indexed: 01/07/2023] Open
Abstract
Resting state networks (RSNs) have been found in human brains during awake resting states. RSNs are composed of spatially distributed regions in which spontaneous activity fluctuations are temporally and dynamically correlated. A new computational framework for reconstructing RSNs with human EEG data has been developed in the present study. The proposed framework utilizes independent component analysis (ICA) on short-time Fourier transformed inverse source maps imaged from EEG data and statistical correlation analysis to generate cortical tomography of electrophysiological RSNs. The proposed framework was evaluated on three sets of resting-state EEG data obtained in the comparison of two conditions: (1) healthy controls with eyes closed and eyes open; (2) healthy controls and individuals with a balance disorder; (3) individuals with a balance disorder before and after receiving repetitive transcranial magnetic stimulation (rTMS) treatment. In these analyses, the same group of five RSNs with similar spatial and spectral patterns were successfully reconstructed by the proposed framework from each individual EEG dataset. These EEG RSN tomographic maps showed significant similarity with RSN templates derived from functional magnetic resonance imaging (fMRI). Furthermore, significant spatial and spectral differences of RSNs among compared conditions were observed in tomographic maps as well as their spectra, which were consistent with findings reported in the literature. Beyond the success of reconstructing EEG RSNs spatially on the cortical surface as in fMRI studies, this novel approach defines RSNs further with spectra, providing a new dimension in understanding and probing basic neural mechanisms of RSNs. The findings in patients' data further demonstrate its potential in identifying biomarkers for the diagnosis and treatment evaluation of neuropsychiatric disorders.
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Affiliation(s)
- Chuang Li
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, United States
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States.,Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, Norman, OK, United States
| | - Guofa Shou
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Yoon-Hee Cha
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Sridhar Sunderam
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY, United States
| | - Walter Besio
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States.,Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, Norman, OK, United States
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van Klink N, Mol A, Ferrier C, Hillebrand A, Huiskamp G, Zijlmans M. Beamforming applied to surface EEG improves ripple visibility. Clin Neurophysiol 2018; 129:101-111. [DOI: 10.1016/j.clinph.2017.10.026] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 09/20/2017] [Accepted: 10/05/2017] [Indexed: 01/17/2023]
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23
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Resting state connectivity mediates the relationship between collectivism and social cognition. Int J Psychophysiol 2017; 123:17-24. [PMID: 29208492 DOI: 10.1016/j.ijpsycho.2017.12.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2017] [Revised: 11/13/2017] [Accepted: 12/02/2017] [Indexed: 01/15/2023]
Abstract
Humans are intrinsically social beings and it is natural that self-processing is associated with social cognition. The degree to which the self is perceived as a part of social environment is modulated by cultural stereotypes, such as collectivism and individualism. Here, we tested the hypothesis that individuals who endorse collectivist values would spontaneously think more about their relationships with other people and this association would be mediated by connectivity between the medial prefrontal cortex (MPFC) and the rest of the brain. Connectivity was evaluated based on resting state EEG data using the recently developed methods, which combine beamformer spatial filtering with seed based connectivity estimation. The formal mediation analysis revealed that collectivism is associated with an enhanced connectivity of MPFC with a set of cortical regions that are frequently co-activated in moral reasoning, empathy, and theory of mind tasks and with diminished connectivity with the precuneus\posterior cingulate cortex, which is involved in self-centered cognition. The relationship between collectivism and social cognition was mediated by MPFC connectivity with the left middle temporal gyrus implying that in participants with collectivistic attitude, thinking about relationships with other people may be associated with semantic memory retrieval and reasoning on moral issues and others' intentions.
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24
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Resting State Networks Mediate the Effect of Genotype by Environment Interaction on Mental Health. Neuroscience 2017; 369:139-151. [PMID: 29129791 DOI: 10.1016/j.neuroscience.2017.11.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 08/21/2017] [Accepted: 11/04/2017] [Indexed: 12/12/2022]
Abstract
A number of studies have shown that the presence of short (S) allele of the serotonin transporter-linked polymorphic region (5-HTTLPR) is associated with a higher risk for depression following exposure to stressful life events. These findings are in line with neuroimaging studies showing that 5-HTTLPR polymorphism has an effect on the connectivity among key areas involved in emotion regulation. Here using mediated moderation analysis, we show that electrophysiological manifestations of resting state networks in the alpha frequency band mediate the effect of 5-HTTLPR by stress interaction on depression/anxiety symptoms in a nonclinical sample. Specifically, at the brain level, both L-allele homozygotes and S-allele carriers are similarly responsive to stress exposure. However, these brain responses seem to act as triggers of psychopathological symptoms in S-allele carriers, but as suppressors in L-allele homozygotes. This finding implies that the interpretation of the effect of gene by environment interaction on psychopathology seems more complicated than behavioral results alone would imply. It is not just differential sensitivity to stress, but rather different ways of coping with stress, which distinguish S-allele carriers and L-allele homozygotes.
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Knyazev GG, Savostyanov AN, Bocharov AV, Slobodskaya HR, Bairova NB. Personality and resting state networks in children: A longitudinal EEG study. PERSONALITY AND INDIVIDUAL DIFFERENCES 2017. [DOI: 10.1016/j.paid.2017.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Knyazev GG, Savostyanov AN, Bocharov AV, Slobodskaya HR, Bairova NB, Tamozhnikov SS, Stepanova VV. Effortful control and resting state networks: A longitudinal EEG study. Neuroscience 2017; 346:365-381. [DOI: 10.1016/j.neuroscience.2017.01.031] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 01/14/2017] [Accepted: 01/17/2017] [Indexed: 10/20/2022]
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Knyazev GG, Savostyanov AN, Bocharov AV, Kuznetsova VB. Depressive symptoms and autobiographical memory: A pilot electroencephalography (EEG) study. J Clin Exp Neuropsychol 2016; 39:242-256. [DOI: 10.1080/13803395.2016.1219318] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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