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Zhang C, Wang Y, Jing X, Yan JH. Brain mechanisms of mental processing: from evoked and spontaneous brain activities to enactive brain activity. PSYCHORADIOLOGY 2023; 3:kkad010. [PMID: 38666106 PMCID: PMC10917368 DOI: 10.1093/psyrad/kkad010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/23/2023] [Accepted: 06/29/2023] [Indexed: 04/28/2024]
Abstract
Within the context of the computer metaphor, evoked brain activity acts as a primary carrier for the brain mechanisms of mental processing. However, many studies have found that evoked brain activity is not the major part of brain activity. Instead, spontaneous brain activity exhibits greater intensity and coevolves with evoked brain activity through continuous interaction. Spontaneous and evoked brain activities are similar but not identical. They are not separate parts, but always dynamically interact with each other. Therefore, the enactive cognition theory further states that the brain is characterized by unified and active patterns of activity. The brain adjusts its activity pattern by minimizing the error between expectation and stimulation, adapting to the ever-changing environment. Therefore, the dynamic regulation of brain activity in response to task situations is the core brain mechanism of mental processing. Beyond the evoked brain activity and spontaneous brain activity, the enactive brain activity provides a novel framework to completely describe brain activities during mental processing. It is necessary for upcoming researchers to introduce innovative indicators and paradigms for investigating enactive brain activity during mental processing.
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Affiliation(s)
- Chi Zhang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Xiujuan Jing
- Tianfu College of Southwestern University of Finance and Economics, Chengdu 610052, China
| | - Jin H Yan
- Sports Psychology Department, China Institute of Sport Science, Beijing 100061, China
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2
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Lee SW, Kim E, Jang TY, Choi H, Kim S, Song H, Hwang MJ, Chang Y, Lee SJ. Alterations of Power Spectral Density in Salience Network during Thought-action Fusion Induction Paradigm in Obsessive-compulsive Disorder. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2022; 20:415-426. [PMID: 35879026 PMCID: PMC9329118 DOI: 10.9758/cpn.2022.20.3.415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/30/2021] [Accepted: 04/29/2021] [Indexed: 11/18/2022]
Abstract
Objective Methods Results Conclusion
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Affiliation(s)
- Sang Won Lee
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Eunji Kim
- Department of Medical and Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Tae Yang Jang
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
| | - Heajung Choi
- Department of Medical and Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Seungho Kim
- Department of Medical and Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Huijin Song
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | | | - Yongmin Chang
- Department of Molecular Medicine, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Radiology, Kyungpook National University Hospital, Daegu, Korea
| | - Seung Jae Lee
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
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3
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The temporal dedifferentiation of global brain signal fluctuations during human brain ageing. Sci Rep 2022; 12:3616. [PMID: 35256664 PMCID: PMC8901682 DOI: 10.1038/s41598-022-07578-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 02/22/2022] [Indexed: 01/18/2023] Open
Abstract
The variation of brain functions as healthy ageing has been discussed widely using resting-state brain imaging. Previous conclusions may be misinterpreted without considering the effects of global signal (GS) on local brain activities. Up to now, the variation of GS with ageing has not been estimated. To fill this gap, we defined the GS as the mean signal of all voxels in the gray matter and systematically investigated correlations between age and indices of GS fluctuations. What's more, these tests were replicated with data after hemodynamic response function (HRF) de-convolution and data without noise regression as well as head motion data to verify effects of non-neural information on age. The results indicated that GS fluctuations varied as ageing in three ways. First, GS fluctuations were reduced with age. Second, the GS power transferred from lower frequencies to higher frequencies with age. Third, the GS power was more evenly distributed across frequencies in ageing brain. These trends were partly influenced by HRF and physiological noise, indicating that the age effects of GS fluctuations are associated with a variety of physiological activities. These results may indicate the temporal dedifferentiation hypothesis of brain ageing from the global perspective.
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Dynamics of task-induced modulation of spontaneous brain activity and functional connectivity in the triple resting-state networks assessed using the visual oddball paradigm. PLoS One 2021; 16:e0246709. [PMID: 34735449 PMCID: PMC8568109 DOI: 10.1371/journal.pone.0246709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 10/16/2021] [Indexed: 11/19/2022] Open
Abstract
The default mode network (DMN), the salience network (SN), and the central executive network (CEN) are considered as the core resting-state brain networks (RSN) due to their involvement in a wide range of cognitive tasks. Despite the large body of knowledge related to their regional spontaneous activity (RSA) and functional connectivity (FC) of these networks, less is known about the dynamics of the task-associated modulation on these parameters and the task-induced interaction between these three networks. We have investigated the effects of the visual-oddball paradigm on three fMRI measures (amplitude of low-frequency fluctuations for RSA, regional homogeneity for local FC, and degree centrality for global FC) in these three core RSN. A rest-task-rest paradigm was used and the RSNs were identified using independent component analysis (ICA) on the resting-state data. The observed patterns of change differed noticeably between the networks and were tightly associated with the task-related brain activity and the distinct involvement of the networks in the performance of the single subtasks. Furthermore, the inter-network analysis showed an increased synchronization of CEN with the DMN and the SN immediately after the task, but not between the DMN and SN. Higher pre-task inter-network synchronization between the DMN and the CEN was associated with shorter reaction times and thus better performance. Our results provide some additional insights into the dynamics within and between the triple RSN. Further investigations are required in order to understand better their functional importance and interplay.
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Di Pietro M, Russo M, Dono F, Carrarini C, Thomas A, Di Stefano V, Telese R, Bonanni L, Sensi SL, Onofrj M, Franciotti R. A Critical Review of Alien Limb-Related Phenomena and Implications for Functional Magnetic Resonance Imaging Studies. Front Neurol 2021; 12:661130. [PMID: 34566830 PMCID: PMC8458742 DOI: 10.3389/fneur.2021.661130] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 07/06/2021] [Indexed: 11/27/2022] Open
Abstract
Consensus criteria on corticobasal degeneration (CBD) include alien limb (AL) phenomena. However, the gist of the behavioral features of AL is still “a matter of debate.” CBD-related AL has so far included the description of involuntary movements, frontal release phenomena (frontal AL), or asomatognosia (posterior or “real” AL). In this context, the most frequent symptoms are language and praxis deficits and cortical sensory misperception. However, asomatognosia requires, by definition, intact perception and cognition. Thus, to make a proper diagnosis of AL in the context of CBD, cognitive and language dysfunctions must be carefully verified and objectively assessed. We reviewed the current literature on AL in CBD and now propose that the generic use of the term AL should be avoided. This catchall AL term should instead be deconstructed. We propose that the term AL is appropriate to describe clinical features associated with specific brain lesions. More discrete sets of regionally bound clinical signs that depend on dysfunctions of specific brain areas need to be assessed and presented when posing the diagnosis. Thus, in our opinion, the AL term should be employed in association with precise descriptions of the accompanying involuntary movements, sensory misperceptions, agnosia-asomatognosia contents, and the presence of utilization behavior. The review also offers an overview of functional magnetic resonance imaging-based studies evaluating AL-related phenomena. In addition, we provide a complementary set of video clips depicting CBD-related involuntary movements that should not mistakenly be interpreted as signs of AL.
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Affiliation(s)
- Martina Di Pietro
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Fedele Dono
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Claudia Carrarini
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Astrid Thomas
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Vincenzo Di Stefano
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Department of Biomedicine, Neuroscience and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Roberta Telese
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,IRCCS C. Mondino Foundation, Pavia, Italy
| | - Laura Bonanni
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy.,YDA Foundation, Institute of Immune Therapy and Advanced Biological Treatment, Pescara, Italy
| | - Raffaella Franciotti
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
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6
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Veselinović T, Rajkumar R, Amort L, Junger J, Shah NJ, Fimm B, Neuner I. Connectivity Patterns in the Core Resting-State Networks and Their Influence on Cognition. Brain Connect 2021; 12:334-347. [PMID: 34182786 DOI: 10.1089/brain.2020.0943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
Introduction: Three prominent resting-state networks (rsNW) (default mode network [DMN], salience network [SN], and central executive network [CEN]) are recognized for their important role in several neuropsychiatric conditions. However, our understanding of their relevance in terms of cognition remains insufficient. Materials and Methods: In response, this study aims at investigating the patterns of different network properties (resting-state activity [RSA] and short- and long-range functional connectivity [FC]) in these three core rsNWs, as well as the dynamics of age-associated changes and their relation to cognitive performance in a sample of healthy controls (N = 74) covering a large age span (20-79 years). Using a whole-network based approach, three measures were calculated from the functional magnetic resonance imaging (fMRI) data: amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and degree of network centrality (DC). The cognitive test battery covered the following domains: memory, executive functioning, processing speed, attention, and visual perception. Results: For all three fMRI measures (ALFF, ReHo, and DC), the highest values of spontaneous brain activity (ALFF), short- and long-range connectivity (ReHo, DC) were observed in the DMN and the lowest in the SN. Significant age-associated decrease was observed in the DMN for ALFF and DC, and in the SN for ALFF and ReHo. Significant negative partial correlations were observed for working memory and ALFF in all three networks, as well as for additional cognitive parameters and ALFF in CEN. Discussion: Our results show that higher RSA in the three core rsNWs may have an unfavorable effect on cognition. Conversely, the pattern of network properties in healthy subjects included low RSA and FC in the SN. This complements previous research related to the three core rsNW and shows that the chosen approach can provide additional insight into their function.
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Affiliation(s)
- Tanja Veselinović
- Department of Psychiatry, Psychotherapy and Psychosomatics and RWTH Aachen University, Aachen, Germany
| | - Ravichandran Rajkumar
- Department of Psychiatry, Psychotherapy and Psychosomatics and RWTH Aachen University, Aachen, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany.,Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich GmbH, Jülich, Germany
| | | | - Jessica Junger
- Department of Psychiatry, Psychotherapy and Psychosomatics and RWTH Aachen University, Aachen, Germany
| | - Nadim Jon Shah
- JARA-BRAIN-Translational Medicine, Aachen, Germany.,Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich GmbH, Jülich, Germany.,Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Bruno Fimm
- JARA-BRAIN-Translational Medicine, Aachen, Germany
| | - Irene Neuner
- Department of Psychiatry, Psychotherapy and Psychosomatics and RWTH Aachen University, Aachen, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany.,Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich GmbH, Jülich, Germany
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7
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Mascali D, Moraschi M, DiNuzzo M, Tommasin S, Fratini M, Gili T, Wise RG, Mangia S, Macaluso E, Giove F. Evaluation of denoising strategies for task-based functional connectivity: Equalizing residual motion artifacts between rest and cognitively demanding tasks. Hum Brain Mapp 2021; 42:1805-1828. [PMID: 33528884 PMCID: PMC7978116 DOI: 10.1002/hbm.25332] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 12/04/2020] [Accepted: 12/17/2020] [Indexed: 11/17/2022] Open
Abstract
In‐scanner head motion represents a major confounding factor in functional connectivity studies and it raises particular concerns when motion correlates with the effect of interest. One such instance regards research focused on functional connectivity modulations induced by sustained cognitively demanding tasks. Indeed, cognitive engagement is generally associated with substantially lower in‐scanner movement compared with unconstrained, or minimally constrained, conditions. Consequently, the reliability of condition‐dependent changes in functional connectivity relies on effective denoising strategies. In this study, we evaluated the ability of common denoising pipelines to minimize and balance residual motion‐related artifacts between resting‐state and task conditions. Denoising pipelines—including realignment/tissue‐based regression, PCA/ICA‐based methods (aCompCor and ICA‐AROMA, respectively), global signal regression, and censoring of motion‐contaminated volumes—were evaluated according to a set of benchmarks designed to assess either residual artifacts or network identifiability. We found a marked heterogeneity in pipeline performance, with many approaches showing a differential efficacy between rest and task conditions. The most effective approaches included aCompCor, optimized to increase the noise prediction power of the extracted confounding signals, and global signal regression, although both strategies performed poorly in mitigating the spurious distance‐dependent association between motion and connectivity. Censoring was the only approach that substantially reduced distance‐dependent artifacts, yet this came at the great cost of reduced network identifiability. The implications of these findings for best practice in denoising task‐based functional connectivity data, and more generally for resting‐state data, are discussed.
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Affiliation(s)
- Daniele Mascali
- MARBILab, CREF - Centro Ricerche Enrico Fermi, Roma, 00184, Italy.,Fondazione Santa Lucia IRCCS, Roma, Italy
| | - Marta Moraschi
- MARBILab, CREF - Centro Ricerche Enrico Fermi, Roma, 00184, Italy.,Fondazione Santa Lucia IRCCS, Roma, Italy
| | - Mauro DiNuzzo
- MARBILab, CREF - Centro Ricerche Enrico Fermi, Roma, 00184, Italy.,Fondazione Santa Lucia IRCCS, Roma, Italy
| | - Silvia Tommasin
- Dipartimento di Neuroscienze umane, Sapienza Università di Roma, Roma, Italy
| | - Michela Fratini
- Fondazione Santa Lucia IRCCS, Roma, Italy.,Istituto di Nanotecnologia, Consiglio Nazionale delle Ricerche, Roma, Italy
| | - Tommaso Gili
- Networks Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Richard G Wise
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK.,Institute for Advanced Biomedical Technologies, "G. D'Annunzio University" of Chieti-Pescara, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Silvia Mangia
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Federico Giove
- MARBILab, CREF - Centro Ricerche Enrico Fermi, Roma, 00184, Italy.,Fondazione Santa Lucia IRCCS, Roma, Italy
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8
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The subsystem mechanism of default mode network underlying rumination: A reproducible neuroimaging study. Neuroimage 2020; 221:117185. [DOI: 10.1016/j.neuroimage.2020.117185] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 07/15/2020] [Accepted: 07/17/2020] [Indexed: 12/28/2022] Open
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9
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Agrawal S, Chinnadurai V, Kaur A, Kumar P, Kaur P, Sharma R, Kumar Singh A. Estimation of Functional Connectivity Modulations During Task Engagement and Their Neurovascular Underpinnings Through Hemodynamic Reorganization Method. Brain Connect 2019; 9:341-355. [PMID: 30688078 DOI: 10.1089/brain.2018.0656] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
This study proposes an approach to understand the effect of task engagement through integrated analysis of modulations in functional networks and associated changes in their neurovascular underpinnings at every voxel. For this purpose, a novel approach that brings reorganization in acquired task-functional magnetic resonance imaging information based on hemodynamic characteristics of every task stimulus is proposed and validated. At first, modulations in functional networks of visual target detection task were estimated at every voxel through proposed methodology. It revealed task stimulus dependency in the modulation of default mode network (DMN). The DMN modulated as task negative network (TNN) during target stimulus. On the contrary, it was not entirely TNN during nontarget stimulus. The frontal-parietal and visual networks modulated as task positive network during both task stimuli. Further, modulations of neurovascular underpinnings associated with engagement of task were estimated by correlating the hemodynamically reorganized task blood oxygen level dependent information with simultaneously acquired electroencephalography frequency powers. It revealed the strong association of neurovascular underpinnings with their modulation of functional networks and the associated neuronal activity during task engagement. Finally, graph theoretical parameters such as local, global efficiency and clustering coefficient were also measured at the specific regions for validating the results of proposed method. Modulation observed in graph theory measures clearly validated the activation and deactivation of functional networks observed by the proposed method during task engagement. Thus, the voxel-wise estimation of task-related modulation of functional networks and associated neurovascular underpinnings through proposed technique provide better insights into neuronal mechanism involved during engagement in a task.
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Affiliation(s)
- Swati Agrawal
- 1 NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | | | - Ardaman Kaur
- 1 NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Pawan Kumar
- 1 NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Prabhjot Kaur
- 1 NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Rinku Sharma
- 2 Delhi Technological University, Shahbad Daulatpur, Delhi, India
| | - Ajay Kumar Singh
- 1 NMR Research Centre, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
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10
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Ulloa A, Horwitz B. Quantifying Differences Between Passive and Task-Evoked Intrinsic Functional Connectivity in a Large-Scale Brain Simulation. Brain Connect 2018; 8:637-652. [PMID: 30430844 DOI: 10.1089/brain.2018.0620] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Establishing a connection between intrinsic and task-evoked brain activities is critical because it would provide a way to map task-related brain regions in patients unable to comply with such tasks. A crucial question within this realm is to what extent the execution of a cognitive task affects the intrinsic activity of brain regions not involved in the task. Computational models can be useful to answer this question because they allow us to distinguish task from nontask neural elements while giving us the effects of task execution on nontask regions of interest at the neuroimaging level. The quantification of those effects in a computational model would represent a step toward elucidating the intrinsic versus task-evoked connection. In this study we used computational modeling and graph theoretical metrics to quantify changes in intrinsic functional brain connectivity due to task execution. We used our large-scale neural modeling framework to embed a computational model of visual short-term memory into an empirically derived connectome. We simulated a neuroimaging study consisting of 10 subjects performing passive fixation (PF), passive viewing (PV), and delayed match-to-sample (DMS) tasks. We used the simulated blood oxygen level-dependent functional magnetic resonance imaging time series to calculate functional connectivity (FC) matrices and used those matrices to compute several graph theoretical measures. After determining that the simulated graph theoretical measures were largely consistent with experiments, we were able to quantify the differences between the graph metrics of the PF condition and those of the PV and DMS conditions. Thus, we show that we can use graph theoretical methods applied to simulated brain networks to aid in the quantification of changes in intrinsic brain FC during task execution. Our results represent a step toward establishing a connection between intrinsic and task-related brain activities.
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Affiliation(s)
- Antonio Ulloa
- Brain Imaging and Modeling Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland.,Neural Bytes, Washington, District of Columbia
| | - Barry Horwitz
- Brain Imaging and Modeling Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland
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11
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Tommasin S, Mascali D, Moraschi M, Gili T, Hassan IE, Fratini M, DiNuzzo M, Wise RG, Mangia S, Macaluso E, Giove F. Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation. Neuroimage 2018; 179:570-581. [PMID: 29908935 DOI: 10.1016/j.neuroimage.2018.06.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 06/04/2018] [Indexed: 01/09/2023] Open
Abstract
Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.
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Affiliation(s)
- Silvia Tommasin
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy; Dipartimento di Neuroscienze umane, Sapienza Università di Roma, Roma, Italy
| | - Daniele Mascali
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy
| | - Marta Moraschi
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy
| | - Tommaso Gili
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy; Fondazione Santa Lucia IRCCS, Roma, Italy
| | | | - Michela Fratini
- Fondazione Santa Lucia IRCCS, Roma, Italy; Istituto di Nanotecnologia, Consiglio Nazionale delle Ricerche, Roma, Italy
| | - Mauro DiNuzzo
- Center for Basic and Translational Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Richard G Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Silvia Mangia
- Center for Magnetic Resonance Research, Dept. of Radiology, University of Minnesota, Minneapolis, USA
| | | | - Federico Giove
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy; Fondazione Santa Lucia IRCCS, Roma, Italy.
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