1
|
Kumar VA, Lee J, Liu HL, Allen JW, Filippi CG, Holodny AI, Hsu K, Jain R, McAndrews MP, Peck KK, Shah G, Shimony JS, Singh S, Zeineh M, Tanabe J, Vachha B, Vossough A, Welker K, Whitlow C, Wintermark M, Zaharchuk G, Sair HI. Recommended Resting-State fMRI Acquisition and Preprocessing Steps for Preoperative Mapping of Language and Motor and Visual Areas in Adult and Pediatric Patients with Brain Tumors and Epilepsy. AJNR Am J Neuroradiol 2024; 45:139-148. [PMID: 38164572 DOI: 10.3174/ajnr.a8067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 10/12/2023] [Indexed: 01/03/2024]
Abstract
Resting-state (rs) fMRI has been shown to be useful for preoperative mapping of functional areas in patients with brain tumors and epilepsy. However, its lack of standardization limits its widespread use and hinders multicenter collaboration. The American Society of Functional Neuroradiology, American Society of Pediatric Neuroradiology, and the American Society of Neuroradiology Functional and Diffusion MR Imaging Study Group recommend specific rs-fMRI acquisition approaches and preprocessing steps that will further support rs-fMRI for future clinical use. A task force with expertise in fMRI from multiple institutions provided recommendations on the rs-fMRI steps needed for mapping of language, motor, and visual areas in adult and pediatric patients with brain tumor and epilepsy. These were based on an extensive literature review and expert consensus.Following rs-fMRI acquisition parameters are recommended: minimum 6-minute acquisition time; scan with eyes open with fixation; obtain rs-fMRI before both task-based fMRI and contrast administration; temporal resolution of ≤2 seconds; scanner field strength of 3T or higher. The following rs-fMRI preprocessing steps and parameters are recommended: motion correction (seed-based correlation analysis [SBC], independent component analysis [ICA]); despiking (SBC); volume censoring (SBC, ICA); nuisance regression of CSF and white matter signals (SBC); head motion regression (SBC, ICA); bandpass filtering (SBC, ICA); and spatial smoothing with a kernel size that is twice the effective voxel size (SBC, ICA).The consensus recommendations put forth for rs-fMRI acquisition and preprocessing steps will aid in standardization of practice and guide rs-fMRI program development across institutions. Standardized rs-fMRI protocols and processing pipelines are essential for multicenter trials and to implement rs-fMRI as part of standard clinical practice.
Collapse
Affiliation(s)
- V A Kumar
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - J Lee
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - H-L Liu
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - J W Allen
- Emory University (J.W.A.), Atlanta, Georgia
| | - C G Filippi
- Tufts University (C.G.F.), Boston, Massachusetts
| | - A I Holodny
- Memorial Sloan Kettering Cancer Center (A.I.H., K.K.P.), New York, New York
| | - K Hsu
- New York University (K.H., R.J.), New York, New York
| | - R Jain
- New York University (K.H., R.J.), New York, New York
| | - M P McAndrews
- University of Toronto (M.P.M.), Toronto, Ontario, Canada
| | - K K Peck
- Memorial Sloan Kettering Cancer Center (A.I.H., K.K.P.), New York, New York
| | - G Shah
- University of Michigan (G.S.), Ann Arbor, Michigan
| | - J S Shimony
- Washington University School of Medicine (J.S.S.), St. Louis, Missouri
| | - S Singh
- University of Texas Southwestern Medical Center (S.S.), Dallas, Texas
| | - M Zeineh
- Stanford University (M.Z., G.Z.), Palo Alto, California
| | - J Tanabe
- University of Colorado (J.T.), Aurora, Colorado
| | - B Vachha
- University of Massachusetts (B.V.), Worcester, Massachusetts
| | - A Vossough
- Children's Hospital of Philadelphia, University of Pennsylvania (A.V.), Philadelphia, Pennsylvania
| | - K Welker
- Mayo Clinic (K.W.), Rochester, Minnesota
| | - C Whitlow
- Wake Forest University (C.W.), Winston-Salem, North Carolina
| | - M Wintermark
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - G Zaharchuk
- Stanford University (M.Z., G.Z.), Palo Alto, California
| | - H I Sair
- Johns Hopkins University (H.I.S.), Baltimore, Maryland
| |
Collapse
|
2
|
Candemir C. Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI. SENSORS (BASEL, SWITZERLAND) 2023; 23:5866. [PMID: 37447716 DOI: 10.3390/s23135866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/17/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023]
Abstract
Spatial smoothing is a preprocessing step applied to neuroimaging data to enhance data quality by reducing noise and artifacts. However, selecting an appropriate smoothing kernel size can be challenging as it can lead to undesired alterations in final images and functional connectivity networks. However, there is no sufficient information about the effects of the Gaussian kernel size on group-level results for different cases yet. This study investigates the influence of kernel size on functional connectivity networks and network parameters in whole-brain rs-fMRI and tb-fMRI analyses of healthy adults. The analysis includes {0, 2, 4, 6, 8, 10} mm kernels, commonly used in practical analyses, covering all major brain networks. Graph theoretical measures such as betweenness centrality, global/local efficiency, clustering coefficient, and average path length are examined for each kernel. Additionally, principal component analysis (PCA) and independent component analysis (ICA) parameters, namely kurtosis and skewness, are evaluated for the functional images. The findings demonstrate that kernel size directly affects node connections, resulting in modifications to functional network structures and PCA/ICA parameters. However, network metrics exhibit greater resilience to these changes.
Collapse
Affiliation(s)
- Cemre Candemir
- International Computer Institute, Ege University, Izmir 35100, Turkey
| |
Collapse
|
3
|
Tansey R, Graff K, Rohr CS, Dimond D, Ip A, Yin S, Dewey D, Bray S. Functional MRI responses to naturalistic stimuli are increasingly typical across early childhood. Dev Cogn Neurosci 2023; 62:101268. [PMID: 37327695 PMCID: PMC10275704 DOI: 10.1016/j.dcn.2023.101268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 04/05/2023] [Accepted: 06/12/2023] [Indexed: 06/18/2023] Open
Abstract
While findings show that throughout development, there are child- and age-specific patterns of brain functioning, there is also evidence for significantly greater inter-individual response variability in young children relative to adults. It is currently unclear whether this increase in functional "typicality" (i.e., inter-individual similarity) is a developmental process that occurs across early childhood, and what changes in BOLD response may be driving changes in typicality. We collected fMRI data from 81 typically developing 4-8-year-old children during passive viewing of age-appropriate television clips and asked whether there is increasing typicality of brain response across this age range. We found that the "increasing typicality" hypothesis was supported across many regions engaged by passive viewing. Post hoc analyses showed that in a priori ROIs related to language and face processing, the strength of the group-average shared component of activity increased with age, with no concomitant decline in residual signal or change in spatial extent or variability. Together, this suggests that increasing inter-individual similarity of functional responses to audiovisual stimuli is an important feature of early childhood functional brain development.
Collapse
Affiliation(s)
- Ryann Tansey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
| | - Kirk Graff
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Christiane S Rohr
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Dennis Dimond
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Amanda Ip
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Shelly Yin
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Deborah Dewey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Community Health Science, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Owerko Centre at the Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Signe Bray
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| |
Collapse
|
4
|
Niu J, Zheng Z, Wang Z, Xu L, Meng Q, Zhang X, Kuang L, Wang S, Dong L, Qiu J, Jiao Q, Cao W. Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan. Front Neurosci 2022; 16:984571. [PMID: 36213738 PMCID: PMC9534554 DOI: 10.3389/fnins.2022.984571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18–87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p < 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p < 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.
Collapse
Affiliation(s)
- Jinpeng Niu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
| | - Zihao Zheng
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Ziqi Wang
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Longchun Xu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Qingmin Meng
- Department of Interventional Radiology, Taian Central Hospital, Tai’an, China
| | - Xiaotong Zhang
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
| | - Liangfeng Kuang
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
| | - Shigang Wang
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
| | - Li Dong
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
| | - Qing Jiao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
| | - Weifang Cao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, China
- *Correspondence: Weifang Cao,
| |
Collapse
|
5
|
Russo AG, De Martino M, Elia A, Di Salle F, Esposito F. Negative correlation between word-level surprisal and intersubject neural synchronization during narrative listening. Cortex 2022; 155:132-149. [DOI: 10.1016/j.cortex.2022.07.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 02/10/2022] [Accepted: 07/06/2022] [Indexed: 11/30/2022]
|
6
|
Weiler M, Casseb RF, de Campos BM, Crone JS, Lutkenhoff ES, Vespa PM, Monti MM. Evaluating denoising strategies in resting-state functional magnetic resonance in traumatic brain injury (EpiBioS4Rx). Hum Brain Mapp 2022; 43:4640-4649. [PMID: 35723510 PMCID: PMC9491287 DOI: 10.1002/hbm.25979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 05/17/2022] [Accepted: 05/29/2022] [Indexed: 11/11/2022] Open
Abstract
Resting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity (FC) of traumatic brain injury (TBI) patients. We applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 TBI patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial. Pipelines were evaluated by three quality control (QC) metrics across three exclusion regimes based on the participant's head movement profile. While no pipeline eliminated noise effects on FC, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data-driven methods performed comparatively worse. In this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related FC in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as TBI datasets.
Collapse
Affiliation(s)
- Marina Weiler
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Raphael F Casseb
- Neuroimaging Laboratory, University of Campinas, Campinas, São Paulo, Brazil
| | - Brunno M de Campos
- Neuroimaging Laboratory, University of Campinas, Campinas, São Paulo, Brazil
| | - Julia S Crone
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Evan S Lutkenhoff
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Paul M Vespa
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Martin M Monti
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA.,Department of Neurosurgery, Brain Injury Research Center, University of California Los Angeles, Los Angeles, California, USA
| | | |
Collapse
|
7
|
Stickland RC, Zvolanek KM, Moia S, Caballero-Gaudes C, Bright MG. Lag-Optimized Blood Oxygenation Level Dependent Cerebrovascular Reactivity Estimates Derived From Breathing Task Data Have a Stronger Relationship With Baseline Cerebral Blood Flow. Front Neurosci 2022; 16:910025. [PMID: 35801183 PMCID: PMC9254683 DOI: 10.3389/fnins.2022.910025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve.
Collapse
Affiliation(s)
- Rachael C. Stickland
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Kristina M. Zvolanek
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Spain
- University of the Basque Country EHU/UPV, Donostia, Spain
| | | | - Molly G. Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| |
Collapse
|
8
|
Tansey R, Graff K, Rohr CS, Dimond D, Ip A, Dewey D, Bray S. Inattentive and hyperactive traits differentially associate with inter-individual functional synchrony during video viewing in young children without ADHD. Cereb Cortex Commun 2022; 3:tgac011. [PMID: 35291396 PMCID: PMC8919299 DOI: 10.1093/texcom/tgac011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/22/2022] [Accepted: 02/24/2022] [Indexed: 12/02/2022] Open
Abstract
Inattention and hyperactivity present on a spectrum and may influence the way children perceive and interact with the world. We investigated whether normative variation in inattentive and hyperactive traits was associated with differences in brain function, while children watched clips from an age-appropriate television program. Functional magnetic resonance imaging (fMRI) data and parent reports of inattention and hyperactivity traits were collected from 81 children 4–7 years of age with no parent-reported diagnoses. Data were analyzed using intersubject correlations (ISCs) in mixed effects models to determine if inattentive and hyperactive traits were associated with idiosyncrasy of fMRI response to the video. We hypothesized that pairs of children with higher average inattention and hyperactivity scores would show less interindividual brain synchrony to one another than pairs with lower average scores on these traits. Video watching engaged widespread visual, auditory, default mode and dorsal prefrontal regions. Inattention and hyperactivity were separably associated with ISC in many of these regions. Our findings suggest that the spectrum of inattention and hyperactivity traits in children without ADHD are differentially associated with neural processing of naturalistic video stimuli, which may have implications for understanding how children with different levels of these traits process audiovisual information in unconstrained conditions.
Collapse
Affiliation(s)
- Ryann Tansey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Kirk Graff
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Christiane S Rohr
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Dennis Dimond
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Amanda Ip
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Deborah Dewey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Community Health Science, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Signe Bray
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| |
Collapse
|
9
|
Cosgrove KT, Kerr KL, Ratliff EL, Moore AJ, Misaki M, DeVille DC, Aupperle RL, Simmons WK, Bodurka J, Morris AS. Effects of Parent Emotion Socialization on the Neurobiology Underlying Adolescent Emotion Processing: A Multimethod fMRI Study. Res Child Adolesc Psychopathol 2022; 50:149-161. [PMID: 35113308 PMCID: PMC9262419 DOI: 10.1007/s10802-020-00736-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/15/2020] [Indexed: 02/03/2023]
Abstract
Parents' emotion socialization (ES) practices impact socioemotional development throughout adolescence. Little is known, however, regarding the neurobiology underlying these effects. This study used functional magnetic resonance imaging (fMRI) to examine how parent ES practices relate to adolescent brain function during emotion processing. Thirty-three adolescents (ages 14-16) reported on ES practices of a focal parent (primarily mothers) using the Emotions as a Child (EAC) Scale. Adolescents also completed a conflict discussion task with this parent, and parents' statements were coded for emotional valence. Adolescents performed two fMRI tasks: a standard emotion processing (EP) task (n = 32) and the Testing Emotional Attunement and Mutuality (TEAM) task (n = 27). The EP task consisted of viewing emotional pictures and either reacting naturally or using cognitive reappraisal to regulate emotional responses. The TEAM task was performed with the parent and included trials during which adolescents were shown that their parent made an error, costing the dyad $5. Parent negative verbalizations during the conflict discussion were associated with greater activity in the thalamus during the emotion reactivity condition of the EP task and in the thalamus, superior medial and superior frontal gyri, anterior insula, and dorsolateral prefrontal cortex during the costly error condition of the TEAM task. Unsupportive ES was associated with greater activity in the supplementary motor area and less activity in the paracentral gyrus and amygdala during the costly error condition of the TEAM task. This study supports the premise that ES influences adolescents' emotion-related neural processing, particularly when using ecologically valid tasks in social contexts.
Collapse
Affiliation(s)
- Kelly T Cosgrove
- Department of Psychology, The University of Tulsa, Tulsa, OK, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
| | - Kara L Kerr
- Department of Psychology, Oklahoma State University, Stillwater, OK, USA.
| | - Erin L Ratliff
- Department of Human Development and Family Science, Oklahoma State University, Tulsa, OK, USA
| | - Andrew J Moore
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Biomedical Sciences, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Danielle C DeVille
- Department of Psychology, The University of Tulsa, Tulsa, OK, USA
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Robin L Aupperle
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Community Medicine, The University of Tulsa, Tulsa, OK, USA
| | - W Kyle Simmons
- Department of Pharmacology and Physiology, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK, USA
| | - Amanda Sheffield Morris
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Human Development and Family Science, Oklahoma State University, Tulsa, OK, USA
| |
Collapse
|
10
|
Mansour L S, Seguin C, Smith RE, Zalesky A. Connectome spatial smoothing (CSS): Concepts, methods, and evaluation. Neuroimage 2022; 250:118930. [PMID: 35077853 DOI: 10.1016/j.neuroimage.2022.118930] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 01/17/2022] [Accepted: 01/21/2022] [Indexed: 10/19/2022] Open
Abstract
Structural connectomes are increasingly mapped at high spatial resolutions comprising many hundreds-if not thousands-of network nodes. However, high-resolution connectomes are particularly susceptible to image registration misalignment, tractography artifacts, and noise, all of which can lead to reductions in connectome accuracy and test-retest reliability. We investigate a network analogue of image smoothing to address these key challenges. Connectome Spatial Smoothing (CSS) involves jointly applying a carefully chosen smoothing kernel to the two endpoints of each tractography streamline, yielding a spatially smoothed connectivity matrix. We develop computationally efficient methods to perform CSS using a matrix congruence transformation and evaluate a range of different smoothing kernel choices on CSS performance. We find that smoothing substantially improves the identifiability, sensitivity, and test-retest reliability of high-resolution connectivity maps, though at a cost of increasing storage burden. For atlas-based connectomes (i.e. low-resolution connectivity maps), we show that CSS marginally improves the statistical power to detect associations between connectivity and cognitive performance, particularly for connectomes mapped using probabilistic tractography. CSS was also found to enable more reliable statistical inference compared to connectomes without any smoothing. We provide recommendations for optimal smoothing kernel parameters for connectomes mapped using both deterministic and probabilistic tractography. We conclude that spatial smoothing is particularly important for the reliability of high-resolution connectomes, but can also provide benefits at lower parcellation resolutions. We hope that our work enables computationally efficient integration of spatial smoothing into established structural connectome mapping pipelines.
Collapse
Affiliation(s)
- Sina Mansour L
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, Australia.
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Victoria, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Andrew Zalesky
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Victoria, Australia
| |
Collapse
|
11
|
Burman DD. Topography of hippocampal connectivity with sensorimotor cortex revealed by optimizing smoothing kernel and voxel size. PLoS One 2021; 16:e0260245. [PMID: 34874961 PMCID: PMC8651104 DOI: 10.1371/journal.pone.0260245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 11/05/2021] [Indexed: 11/18/2022] Open
Abstract
Studies of the hippocampus use smaller voxel sizes and smoothing kernels than cortical activation studies, typically using a multivoxel seed with specified radius for connectivity analysis. This study identified optimal processing parameters for evaluating hippocampal connectivity with sensorimotor cortex (SMC), comparing effectiveness by varying parameters during both activation and connectivity analysis. Using both 3mm and 4mm isovoxels, smoothing kernels of 0-10mm were evaluated on the amplitude and extent of motor activation and hippocampal connectivity with SMC. Psychophysiological interactions (PPI) identified hippocampal connectivity with SMC during volitional movements, and connectivity effects from multivoxel seeds were compared with alternate methods; a structural seed represented the mean connectivity map from all voxels within a region, whereas a functional seed represented the regional voxel with maximal SMC connectivity. With few exceptions, the same parameters were optimal for activation and connectivity. Larger isovoxels showed larger activation volumes in both SMC and the hippocampus; connectivity volumes from structural seeds were also larger, except from the posterior hippocampus. Regardless of voxel size, the 10mm smoothing kernel generated larger activation and connectivity volumes from structural seeds, as well as larger beta estimates at connectivity maxima; structural seeds also produced larger connectivity volumes than multivoxel seeds. Functional seeds showed lesser effects from voxel size and smoothing kernels. Optimal parameters revealed topography in structural seed connectivity along both the longitudinal axis and mediolateral axis of the hippocampus. These results indicate larger voxels and smoothing kernels can improve sensitivity for detecting both cortical activation and hippocampal connectivity.
Collapse
Affiliation(s)
- Douglas D. Burman
- Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, United States of America
- * E-mail:
| |
Collapse
|
12
|
Nastase SA, Liu YF, Hillman H, Zadbood A, Hasenfratz L, Keshavarzian N, Chen J, Honey CJ, Yeshurun Y, Regev M, Nguyen M, Chang CHC, Baldassano C, Lositsky O, Simony E, Chow MA, Leong YC, Brooks PP, Micciche E, Choe G, Goldstein A, Vanderwal T, Halchenko YO, Norman KA, Hasson U. The "Narratives" fMRI dataset for evaluating models of naturalistic language comprehension. Sci Data 2021; 8:250. [PMID: 34584100 PMCID: PMC8479122 DOI: 10.1038/s41597-021-01033-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 08/18/2021] [Indexed: 02/08/2023] Open
Abstract
The "Narratives" collection aggregates a variety of functional MRI datasets collected while human subjects listened to naturalistic spoken stories. The current release includes 345 subjects, 891 functional scans, and 27 diverse stories of varying duration totaling ~4.6 hours of unique stimuli (~43,000 words). This data collection is well-suited for naturalistic neuroimaging analysis, and is intended to serve as a benchmark for models of language and narrative comprehension. We provide standardized MRI data accompanied by rich metadata, preprocessed versions of the data ready for immediate use, and the spoken story stimuli with time-stamped phoneme- and word-level transcripts. All code and data are publicly available with full provenance in keeping with current best practices in transparent and reproducible neuroimaging.
Collapse
Affiliation(s)
- Samuel A Nastase
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA.
| | - Yun-Fei Liu
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Hanna Hillman
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Asieh Zadbood
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Liat Hasenfratz
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Neggin Keshavarzian
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Janice Chen
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Christopher J Honey
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Yaara Yeshurun
- School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Mor Regev
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Mai Nguyen
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Claire H C Chang
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | | | - Olga Lositsky
- Department of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence, RI, USA
| | - Erez Simony
- Faculty of Electrical Engineering, Holon Institute of Technology, Holon, Israel
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
| | | | - Yuan Chang Leong
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Paula P Brooks
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Emily Micciche
- Peabody College, Vanderbilt University, Nashville, TN, USA
| | - Gina Choe
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Ariel Goldstein
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Tamara Vanderwal
- Department of Psychiatry, University of British Columbia, and BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Yaroslav O Halchenko
- Department of Psychological and Brain Sciences and Department of Computer Science, Dartmouth College, Hanover, NH, USA
| | - Kenneth A Norman
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Uri Hasson
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| |
Collapse
|
13
|
Shojaeilangari S, Radman N, Taghizadeh ME, Soltanian-Zadeh H. rsfMRI based evidence for functional connectivity alterations in adults with developmental stuttering. Heliyon 2021; 7:e07855. [PMID: 34504967 PMCID: PMC8414185 DOI: 10.1016/j.heliyon.2021.e07855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 05/28/2021] [Accepted: 08/19/2021] [Indexed: 11/16/2022] Open
Abstract
Persistent developmental stuttering (PDS) is defined as a speech disorder mainly characterized by intermittent involuntary disruption in normal fluency, time patterning, and rhythm of speech. Although extensive functional neuroimaging studies have explored brain activation alterations in stuttering, the main affected brain regions/networks in PDS still remain unclear. Here, using functional magnetic resonance imaging (fMRI), we investigated resting-state whole-brain functional connectivity of 15 adults who stutter (PDS group) and 15 age-matched control individuals to reveal the connectivity abnormalities associated with stuttering. We were also interested in exploring how the severity of stuttering varies across individuals to understand the compensatory mechanism of connectivity pattern in patients showing less symptoms. Our results revealed decreased connectivity of left frontal pole and left middle frontal gyrus (MidFG) with right precentral/postcentral gyrus in stuttering individuals compared with control participants, while less symptomatic PDS individuals showed greater functional connectivity between left MidFG and left caudate. Additionally, our finding indicated reduced connectivity in the PDS group between the left superior temporal gyrus (STG) and several brain regions including the right limbic lobe, right fusiform, and right cerebellum, as well as the left middle temporal gyrus (MTG). We also observed that PDS individuals with less severe symptoms had stronger connectivity between right MTG and several left hemispheric regions including inferior frontal gyrus (IFG) and STG. The connectivity between right fronto-orbital and right MTG was also negatively correlated with stuttering severity. These findings may suggest the involvement of right MTG and left MidFG in successful compensatory mechanisms in more fluent stutterers.
Collapse
Affiliation(s)
- Seyedehsamaneh Shojaeilangari
- School of Cognitive Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 1954851167, Tehran, Iran
| | - Narges Radman
- School of Cognitive Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 1954851167, Tehran, Iran
- Department of Psychiatry, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Hamid Soltanian-Zadeh
- School of Cognitive Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 1954851167, Tehran, Iran
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, Tehran University, Tehran, Iran
- Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, Michigan, USA
| |
Collapse
|
14
|
Isherwood SJS, Keuken MC, Bazin PL, Forstmann BU. Cortical and subcortical contributions to interference resolution and inhibition - An fMRI ALE meta-analysis. Neurosci Biobehav Rev 2021; 129:245-260. [PMID: 34310977 DOI: 10.1016/j.neubiorev.2021.07.021] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/08/2021] [Accepted: 07/16/2021] [Indexed: 01/19/2023]
Abstract
Interacting with our environment requires the selection of appropriate responses and the inhibition of others. Such effortful inhibition is achieved by a number of interference resolution and global inhibition processes. This meta-analysis including 57 studies and 73 contrasts revisits the overlap and differences in brain areas supporting interference resolution and global inhibition in cortical and subcortical brain areas. Activation likelihood estimation was used to discern the brain regions subserving each type of cognitive control. Individual contrast analysis revealed a common activation of the bilateral insula and supplementary motor areas. Subtraction analyses demonstrated the voxel-wise differences in recruitment in a number of areas including the precuneus in the interference tasks and the frontal pole and dorsal striatum in the inhibition tasks. Our results display a surprising lack of subcortical involvement within these types of cognitive control, a finding that is likely to reflect a systematic gap in the field of functional neuroimaging.
Collapse
Affiliation(s)
- S J S Isherwood
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, the Netherlands.
| | - M C Keuken
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, the Netherlands
| | - P L Bazin
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, the Netherlands; Max Planck Institute for Human, Cognitive and Brain Sciences, Leipzig, Germany
| | - B U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, the Netherlands
| |
Collapse
|
15
|
Kark SM, Birnie MT, Baram TZ, Yassa MA. Functional Connectivity of the Human Paraventricular Thalamic Nucleus: Insights From High Field Functional MRI. Front Integr Neurosci 2021; 15:662293. [PMID: 33967711 PMCID: PMC8096909 DOI: 10.3389/fnint.2021.662293] [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: 02/01/2021] [Accepted: 03/29/2021] [Indexed: 12/30/2022] Open
Abstract
The paraventricular thalamic nucleus (PVT) is a small but highly connected nucleus of the dorsal midline thalamus. The PVT has garnered recent attention as a context-sensitive node within the thalamocortical arousal system that modulates state-dependent motivated behaviors. Once considered related to generalized arousal responses with non-specific impacts on behavior, accumulating evidence bolsters the contemporary view that discrete midline thalamic subnuclei belong to specialized corticolimbic and corticostriatal circuits related to attention, emotions, and cognition. However, the functional connectivity patterns of the human PVT have yet to be mapped. Here, we combined high-quality, high-resolution 7T and 3T resting state MRI data from 121 young adult participants from the Human Connectome Project (HCP) and thalamic subnuclei atlas masks to investigate resting state functional connectivity of the human PVT. The 7T results demonstrated extensive positive functional connectivity with the brainstem, midbrain, ventral and dorsal medial prefrontal cortex (mPFC), anterior and posterior cingulate, ventral striatum, hippocampus, and amygdala. These connections persist upon controlling for functional connectivity of the rest of the thalamus. Whole-brain contrasts provided further evidence that, compared to three nearby midline thalamic subnuclei, functional connectivity of the PVT is strong with the hippocampus, amygdala, ventral and dorsal mPFC, and middle temporal gyrus. These findings suggest that, even during rest, the human PVT is functionally coupled with many regions known to be structurally connected to rodent and non-human primate PVT. Further, cosine similarity analysis results suggested the PVT is integrated into the default mode network (DMN), an intrinsic connectivity network associated with episodic memory and self-referential thought. The current work provides a much-needed foundation for ongoing and future work examining the functional roles of the PVT in humans.
Collapse
Affiliation(s)
- Sarah M. Kark
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, United States
| | - Matthew T. Birnie
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
| | - Tallie Z. Baram
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
- Department of Anatomy & Neurobiology, University of California, Irvine, Irvine, CA, United States
| | - Michael A. Yassa
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, United States
- Department of Anatomy & Neurobiology, University of California, Irvine, Irvine, CA, United States
| |
Collapse
|
16
|
Alahmadi AAS. Effects of different smoothing on global and regional resting functional connectivity. Neuroradiology 2020; 63:99-109. [PMID: 32840683 DOI: 10.1007/s00234-020-02523-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/13/2020] [Indexed: 01/25/2023]
Abstract
PURPOSE Spatial smoothing is an essential pre-processing step in the process of analysing functional magnetic resonance imaging (fMRI) data, both during an experimental task or during resting-state fMRI (rsfMRI). The main benefit of this spatial smoothing step is to artificially increase the signal-to-noise ratio of the fMRI signal. Previous fMRI studies have investigated the impact of spatial smoothing on task fMRI data, while rsfMRI studies usually apply the same analytical process used for the task data. However, this study investigates changes in different rsfMRI analyses, such as ROI-to-ROI, seed-to-voxels and ICA analyses. METHODS Nineteen healthy volunteers were scanned using rsfMRI with three applied smoothing kernels: 0 mm, 4 mm and 8 mm. Appropriate statistical comparisons were made. RESULTS The findings showed that spatial smoothing has a greater effect on rsfMRI data when analysed using seed-to-voxel-based analysis. The effect was less pronounced when analysing data using ROI-ROI or ICA analyses. The results demonstrated that even when analysing the data without the application of spatial smoothing, the results were significant compared with data analysed using a typical smoothing kernel. However, data analysed with lower-smoothing kernels produced greater negative correlations, particularly with the ICA analysis. CONCLUSION The results suggest that a medium smoothing kernel (around 4 mm) may be preferable, as it is comparable with the 8 mm kernel in all of the analyses performed. It is also recommended that the researchers consider analysing the data using two different smoothing kernels, as this will help to confirm the significance of the results and avoid overestimating the findings.
Collapse
Affiliation(s)
- Adnan A S Alahmadi
- Department of Radiologic Sciences, College of Applied Medical Science, King Abdulaziz University (KAU), Jeddah, Saudi Arabia.
| |
Collapse
|
17
|
Kostorz K, Flanagin VL, Glasauer S. Synchronization between instructor and observer when learning a complex bimanual skill. Neuroimage 2020; 216:116659. [DOI: 10.1016/j.neuroimage.2020.116659] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 02/03/2020] [Accepted: 02/13/2020] [Indexed: 12/24/2022] Open
|
18
|
Triana AM, Glerean E, Saramäki J, Korhonen O. Effects of spatial smoothing on group-level differences in functional brain networks. Netw Neurosci 2020; 4:556-574. [PMID: 32885115 PMCID: PMC7462426 DOI: 10.1162/netn_a_00132] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 02/20/2020] [Indexed: 12/19/2022] Open
Abstract
Brain connectivity with functional magnetic resonance imaging (fMRI) is a popular approach for detecting differences between healthy and clinical populations. Before creating a functional brain network, the fMRI time series must undergo several preprocessing steps to control for artifacts and to improve data quality. However, preprocessing may affect the results in an undesirable way. Spatial smoothing, for example, is known to alter functional network structure. Yet, its effects on group-level network differences remain unknown. Here, we investigate the effects of spatial smoothing on the difference between patients and controls for two clinical conditions: autism spectrum disorder and bipolar disorder, considering fMRI data smoothed with Gaussian kernels (0–32 mm). We find that smoothing affects network differences between groups. For weighted networks, incrementing the smoothing kernel makes networks more different. For thresholded networks, larger smoothing kernels lead to more similar networks, although this depends on the network density. Smoothing also alters the effect sizes of the individual link differences. This is independent of the region of interest (ROI) size, but varies with link length. The effects of spatial smoothing are diverse, nontrivial, and difficult to predict. This has important consequences: The choice of smoothing kernel affects the observed network differences. Spatial smoothing is a preprocessing tool commonly applied to reduce the amount of noise in functional magnetic resonance imaging (fMRI) data. However, smoothing is known to affect the outcomes of functional brain network analysis at the level of individual subjects in undesired ways. Here, we investigate how spatial smoothing affects the observed differences in brain network structure between subject groups. Using fMRI data from two clinical populations and healthy controls, we show that the between-group differences in network structure depend on the amount of spatial smoothing applied during preprocessing in a nontrivial way. The optimal level of spatial smoothing is difficult to define and probably depends on a set of analysis parameters. Therefore, we recommend applying spatial smoothing only after careful consideration.
Collapse
Affiliation(s)
- Ana María Triana
- Department of Computer Science, School of Science, Aalto University, Espoo, Finland
| | - Enrico Glerean
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Espoo, Finland
| | - Jari Saramäki
- Department of Computer Science, School of Science, Aalto University, Espoo, Finland
| | - Onerva Korhonen
- Université de Lille, CNRS, UMR 9193 - SCALab - Sciences Cognitives et Sciences Affectives, Lille, France
| |
Collapse
|
19
|
First-Person Virtual Embodiment Modulates the Cortical Network that Encodes the Bodily Self and Its Surrounding Space during the Experience of Domestic Violence. eNeuro 2020; 7:ENEURO.0263-19.2019. [PMID: 32312823 PMCID: PMC7240289 DOI: 10.1523/eneuro.0263-19.2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Revised: 11/16/2019] [Accepted: 12/17/2019] [Indexed: 11/24/2022] Open
Abstract
Social aggression, such as domestic violence, has been associated with a reduced ability to take on others’ perspectives. In this naturalistic imaging study, we investigated whether training human participants to take on a first-person embodied perspective during the experience of domestic violence enhances the identification with the victim and elicits brain activity associated with the monitoring of the body and surrounding space and the experience of threat. We combined fMRI measurements with preceding virtual reality exposure from either first-person perspective (1PP) or third-person perspective (3PP) to manipulate whether the domestic abuse stimulus was perceived as directed to oneself or another. We found that 1PP exposure increased body ownership and identification with the virtual victim. Furthermore, when the stimulus was perceived as directed toward oneself, the brain network that encodes the bodily self and its surrounding space was more strongly synchronized across participants and connectivity increased from premotor cortex (PM) and intraparietal sulcus towards superior parietal lobe. Additionally, when the stimulus came near the body, brain activity in the amygdala (AMG) strongly synchronized across participants. Exposure to 3PP reduced synchronization of brain activity in the personal space network, increased modulation of visual areas and strengthened functional connectivity between PM, supramarginal gyrus and primary visual cortex. In conclusion, our results suggest that 1PP embodiment training enhances experience from the viewpoint of the virtual victim, which is accompanied by synchronization in the fronto-parietal network to predict actions toward the body and in the AMG to signal the proximity of the stimulus.
Collapse
|
20
|
Dissociable neural systems for unconditioned acute and sustained fear. Neuroimage 2020; 216:116522. [PMID: 31926280 DOI: 10.1016/j.neuroimage.2020.116522] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 12/19/2019] [Accepted: 01/03/2020] [Indexed: 11/22/2022] Open
Abstract
Fear protects organisms by increasing vigilance and preparedness, and by coordinating survival responses during life-threatening encounters. The fear circuit must thus operate on multiple timescales ranging from preparatory sustained alertness to acute fight-or-flight responses. Here we studied the brain basis of sustained and acute fear using naturalistic functional magnetic resonance imaging (fMRI) enabling analysis of different time-scales of fear responses. Subjects (N = 37) watched feature-length horror movies while their hemodynamic brain activity was measured with fMRI. Time-variable intersubject correlation (ISC) was used to quantify the reliability of brain activity across participants, and seed-based phase synchronization was used for characterizing dynamic connectivity. Subjective ratings of fear were used to assess how synchronization and functional connectivity varied with emotional intensity. These data suggest that acute and sustained fear are supported by distinct neural pathways, with sustained fear amplifying mainly sensory responses, and acute fear increasing activity in brainstem, thalamus, amygdala and cingulate cortices. Sustained fear increased ISC in regions associated with acute fear, and also amplified functional connectivity within this network. The results were replicated in an independent experiment with a different subject sample and stimulus movie. The functional interplay between cortical networks involved in sustained anticipation of, and acute response to, threat involves a complex and dynamic interaction that depends on the proximity of threat, and the need to employ threat appraisals and vigilance for decision making and response selection.
Collapse
|
21
|
Boes AD, Fischer D, Geerling JC, Bruss J, Saper CB, Fox MD. Connectivity of sleep- and wake-promoting regions of the human hypothalamus observed during resting wakefulness. Sleep 2019; 41:5021065. [PMID: 29850898 DOI: 10.1093/sleep/zsy108] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Indexed: 11/13/2022] Open
Abstract
The hypothalamus is a central hub for regulating sleep-wake patterns, the circuitry of which has been investigated extensively in experimental animals. This work has identified a wake-promoting region in the posterior hypothalamus, with connections to other wake-promoting regions, and a sleep-promoting region in the anterior hypothalamus, with inhibitory projections to the posterior hypothalamus. It is unclear whether a similar organization exists in humans. Here, we use anatomical landmarks to identify homologous sleep- and wake-promoting regions of the human hypothalamus and investigate their functional relationships using resting-state functional connectivity magnetic resonance imaging in healthy awake participants. First, we identify a negative correlation (anticorrelation) between the anterior and posterior hypothalamus, two regions with opposing roles in sleep-wake regulation. Next, we show that hypothalamic connectivity predicts a pattern of regional sleep-wake changes previously observed in humans. Specifically, regions that are more positively correlated with the posterior hypothalamus and more negatively correlated with the anterior hypothalamus correspond to regions with the greatest change in cerebral blood flow between sleep-wake states. Taken together, these findings provide preliminary evidence relating a hypothalamic circuit investigated in animals to sleep-wake neuroimaging results in humans, with implications for our understanding of human sleep-wake regulation and the functional significance of anticorrelations.
Collapse
Affiliation(s)
- Aaron D Boes
- Department of Pediatrics, Iowa Neuroimaging and Noninvasive Brain Stimulation Program, University of Iowa Hospitals and Clinics, Iowa City, IA.,Department of Neurology, Iowa Neuroimaging and Noninvasive Brain Stimulation Program, University of Iowa Hospitals and Clinics, Iowa City, IA.,Department of Psychiatry, Iowa Neuroimaging and Noninvasive Brain Stimulation Program, University of Iowa Hospitals and Clinics, Iowa City, IA
| | - David Fischer
- Department of Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA
| | - Joel C Geerling
- Department of Neurology, University of Iowa Hospitals and Clinics, Iowa City, IA
| | - Joel Bruss
- Department of Neurology, Iowa Neuroimaging and Noninvasive Brain Stimulation Program, University of Iowa Hospitals and Clinics, Iowa City, IA
| | - Clifford B Saper
- Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA
| | - Michael D Fox
- Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA.,Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| |
Collapse
|
22
|
Smirnov D, Saarimäki H, Glerean E, Hari R, Sams M, Nummenmaa L. Emotions amplify speaker-listener neural alignment. Hum Brain Mapp 2019; 40:4777-4788. [PMID: 31400052 DOI: 10.1002/hbm.24736] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 07/14/2019] [Accepted: 07/15/2019] [Indexed: 01/08/2023] Open
Abstract
Individuals often align their emotional states during conversation. Here, we reveal how such emotional alignment is reflected in synchronization of brain activity across speakers and listeners. Two "speaker" subjects told emotional and neutral autobiographical stories while their hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). The stories were recorded and played back to 16 "listener" subjects during fMRI. After scanning, both speakers and listeners rated the moment-to-moment valence and arousal of the stories. Time-varying similarity of the blood-oxygenation-level-dependent (BOLD) time series was quantified by intersubject phase synchronization (ISPS) between speaker-listener pairs. Telling and listening to the stories elicited similar emotions across speaker-listener pairs. Arousal was associated with increased speaker-listener neural synchronization in brain regions supporting attentional, auditory, somatosensory, and motor processing. Valence was associated with increased speaker-listener neural synchronization in brain regions involved in emotional processing, including amygdala, hippocampus, and temporal pole. Speaker-listener synchronization of subjective feelings of arousal was associated with increased neural synchronization in somatosensory and subcortical brain regions; synchronization of valence was associated with neural synchronization in parietal cortices and midline structures. We propose that emotion-dependent speaker-listener neural synchronization is associated with emotional contagion, thereby implying that listeners reproduce some aspects of the speaker's emotional state at the neural level.
Collapse
Affiliation(s)
- Dmitry Smirnov
- Department of Neuroscience and Biomedical Engineering (NBE), and Aalto NeuroImaging, Aalto University, Espoo, Finland
| | - Heini Saarimäki
- Department of Neuroscience and Biomedical Engineering (NBE), and Aalto NeuroImaging, Aalto University, Espoo, Finland
| | - Enrico Glerean
- Department of Neuroscience and Biomedical Engineering (NBE), and Aalto NeuroImaging, Aalto University, Espoo, Finland
| | - Riitta Hari
- Department of Neuroscience and Biomedical Engineering (NBE), and Aalto NeuroImaging, Aalto University, Espoo, Finland.,Department of Art, Aalto University, Espoo, Finland
| | - Mikko Sams
- Department of Neuroscience and Biomedical Engineering (NBE), and Aalto NeuroImaging, Aalto University, Espoo, Finland
| | - Lauri Nummenmaa
- Turku PET Centre and Department of Psychology, University of Turku, Turku, Finland.,Turku University Hospital, University of Turku, Turku, Finland
| |
Collapse
|
23
|
Nastase SA, Gazzola V, Hasson U, Keysers C. Measuring shared responses across subjects using intersubject correlation. Soc Cogn Affect Neurosci 2019; 14:667-685. [PMID: 31099394 PMCID: PMC6688448 DOI: 10.1093/scan/nsz037] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 05/10/2019] [Accepted: 05/13/2019] [Indexed: 12/18/2022] Open
Abstract
Our capacity to jointly represent information about the world underpins our social experience. By leveraging one individual's brain activity to model another's, we can measure shared information across brains-even in dynamic, naturalistic scenarios where an explicit response model may be unobtainable. Introducing experimental manipulations allows us to measure, for example, shared responses between speakers and listeners or between perception and recall. In this tutorial, we develop the logic of intersubject correlation (ISC) analysis and discuss the family of neuroscientific questions that stem from this approach. We also extend this logic to spatially distributed response patterns and functional network estimation. We provide a thorough and accessible treatment of methodological considerations specific to ISC analysis and outline best practices.
Collapse
Affiliation(s)
- Samuel A Nastase
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ 08544, USA
| | - Valeria Gazzola
- Social Brain Lab, Netherlands Institute for Neuroscience, KNAW, 105BA Amsterdam, The Netherlands
- Department of Psychology, University of Amsterdam, 1018 WV Amsterdam, The Netherlands
| | - Uri Hasson
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ 08544, USA
| | - Christian Keysers
- Social Brain Lab, Netherlands Institute for Neuroscience, KNAW, 105BA Amsterdam, The Netherlands
- Department of Psychology, University of Amsterdam, 1018 WV Amsterdam, The Netherlands
| |
Collapse
|
24
|
Fu S, Ma X, Wu Y, Bai Z, Yi Y, Liu M, Lan Z, Hua K, Huang S, Li M, Jiang G. Altered Local and Large-Scale Dynamic Functional Connectivity Variability in Posttraumatic Stress Disorder: A Resting-State fMRI Study. Front Psychiatry 2019; 10:234. [PMID: 31031661 PMCID: PMC6474202 DOI: 10.3389/fpsyt.2019.00234] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 03/28/2019] [Indexed: 11/18/2022] Open
Abstract
Posttraumatic stress disorder (PTSD) is a psychiatric condition that can emerge after exposure to an exceedingly traumatic event. Previous neuroimaging studies have indicated that PTSD is characterized by aberrant resting-state functional connectivity (FC). However, few existing studies on PTSD have examined dynamic changes in resting-state FC related to network formation, interaction, and dissolution over time. In this study, we compared the dynamic resting-state local and large-scale FC between PTSD patients (n = 22) and healthy controls (HC; n = 22; conducted as standard deviation in resting-state local and large-scale FC over a series of sliding windows). Local dynamic FC was examined by calculating the dynamic regional homogeneity (dReHo), and large-scale dynamic FC (dFC) was investigated between regions with significant dReHo group differences. For the PTSD patients, we also investigated the relationship between symptom severity and dFC/dReHo. Our results showed that PTSD patients were characterized by I) increased dynamic (more variable) dReHo in left precuneus (PCu); II) increased dynamic (more variable) dFC between the left PCu and left insula; and III) decreased dFC between left PCu and left inferior parietal lobe (IPL), and decreased dFC between left PCu and right PCu. However, there is no significant correlation between the clinical indicators and dReHo/dFC after the family-wise-error (FWE) correction. These findings provided the initial evidence that PTSD is characterized by aberrant patterns of fluctuating communication within brain system such as the default mode network (DMN) and among different brain systems such as the salience network and the DMN.
Collapse
Affiliation(s)
- Shishun Fu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Xiaofen Ma
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yunfan Wu
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Zhigang Bai
- The Department of Medical Imaging of Affiliated Hospital, Inner Mongolia University for Nationalities, Hohhot, China
| | - Yin Yi
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Mengchen Liu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Zhihong Lan
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Kelei Hua
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Shumei Huang
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
- Guangdong Medical University, Dongguan, China
| | - Meng Li
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guihua Jiang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| |
Collapse
|
25
|
Gozdas E, Holland SK, Altaye M. Developmental changes in functional brain networks from birth through adolescence. Hum Brain Mapp 2018; 40:1434-1444. [PMID: 30582266 DOI: 10.1002/hbm.24457] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 10/19/2018] [Accepted: 10/23/2018] [Indexed: 02/02/2023] Open
Abstract
Investigation of the brain connectome using functional magnetic resonance imaging (fMRI) and measures derived from graph theory analysis has emerged as a new approach to study brain development, cognitive function, and neurophysiological disorders. Here we use graph theory analysis to examine the influence of age, sex, and neurocognitive measures on developmental changes to the global and regional topology of functional brain networks derived from fMRI data recorded in 189 healthy subjects from the age of 0-18 years during rest. We observed that Global Efficiency and Rich-Club coefficient increased with age and Local Efficiency and Small-Worldness decreased with age, while Modularity at the global level showed an inverted U-shaped trajectory during development. Marginally significant differences were observed in Local Efficiency, Small-Worldness, and Modularity at a global level between boys and girls throughout development. We also examine the effects of neurocognitive measures in boys and girls globally and locally. Our results provide new insight to understand brain maturation of functional brain connectome and its relation to cognitive development from birth through adolescence.
Collapse
Affiliation(s)
- Elveda Gozdas
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California
| | - Scott K Holland
- Medpace Imaging Core Laboratory, Medpace Inc, Cincinnati, Ohio
| | - Mekibib Altaye
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | | |
Collapse
|
26
|
Ren Y, Nguyen VT, Sonkusare S, Lv J, Pang T, Guo L, Eickhoff SB, Breakspear M, Guo CC. Effective connectivity of the anterior hippocampus predicts recollection confidence during natural memory retrieval. Nat Commun 2018; 9:4875. [PMID: 30451864 PMCID: PMC6242820 DOI: 10.1038/s41467-018-07325-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2018] [Accepted: 10/26/2018] [Indexed: 11/25/2022] Open
Abstract
Human interactions with the world are influenced by memories of recent events. This effect, often triggered by perceptual cues, occurs naturally and without conscious effort. However, the neuroscience of involuntary memory in a dynamic milieu has received much less attention than the mechanisms of voluntary retrieval with deliberate purpose. Here, we investigate the neural processes driven by naturalistic cues that relate to, and presumably trigger the retrieval of recent experiences. Viewing the continuation of recently viewed clips evokes greater bilateral activation in anterior hippocampus, precuneus and angular gyrus than naïve clips. While these regions manifest reciprocal connectivity, continued viewing specifically modulates the effective connectivity from the anterior hippocampus to the precuneus. The strength of this modulation predicts participants' confidence in later voluntary recall of news details. Our study reveals network mechanisms of dynamic, involuntary memory retrieval and its relevance to metacognition in a rich context resembling everyday life.
Collapse
Affiliation(s)
- Yudan Ren
- School of Automation, Northwestern Polytechnical University, 710072, Xi'an, China
- QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia
| | - Vinh T Nguyen
- QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia
| | - Saurabh Sonkusare
- QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia
- School of Medicine, The University of Queensland, Brisbane, 4072, Australia
| | - Jinglei Lv
- QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia
| | - Tianji Pang
- School of Automation, Northwestern Polytechnical University, 710072, Xi'an, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, 710072, Xi'an, China
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, 52425, Germany
| | | | - Christine C Guo
- School of Automation, Northwestern Polytechnical University, 710072, Xi'an, China.
- QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia.
| |
Collapse
|
27
|
Xu H, Su J, Qin J, Li M, Zeng LL, Hu D, Shen H. Impact of global signal regression on characterizing dynamic functional connectivity and brain states. Neuroimage 2018; 173:127-145. [PMID: 29476914 DOI: 10.1016/j.neuroimage.2018.02.036] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2017] [Revised: 01/26/2018] [Accepted: 02/17/2018] [Indexed: 01/08/2023] Open
Abstract
Recently, resting-state functional magnetic resonance imaging (fMRI) studies have been extended to explore fluctuations in correlations over shorter timescales, referred to as dynamic functional connectivity (dFC). However, the impact of global signal regression (GSR) on dFC is not well established, despite the intensive investigations of the influence of GSR on static functional connectivity (sFC). This study aimed to examine the effect of GSR on the performance of the sliding-window correlation, a commonly used method for capturing functional connectivity (FC) dynamics based on resting-state fMRI and simultaneous electroencephalograph (EEG)-fMRI data. The results revealed that the impact of GSR on dFC was spatially heterogeneous, with some susceptible regions including the occipital cortex, sensorimotor area, precuneus, posterior insula and superior temporal gyrus, and that the impact was temporally modulated by the mean global signal (GS) magnitude across windows. Furthermore, GSR substantially changed the connectivity structures of the FC states responding to a high GS magnitude, as well as their temporal features, and even led to the emergence of new FC states. Conversely, those FC states marked by obvious anti-correlation structures associated with the default model network (DMN) were largely unaffected by GSR. Finally, we reported an association between the fluctuations in the windowed magnitude of GS and the time-varying EEG power within subjects, which implied changes in mental states underlying GS dynamics. Overall, this study suggested a potential neuropsychological basis, in addition to nuisance sources, for GS dynamics and highlighted the need for caution in applying GSR to sliding-window correlation analyses. At a minimum, the mental fluctuations of an individual subject, possibly related to ongoing vigilance, should be evaluated during the entire scan when the dynamics of FC is estimated.
Collapse
Affiliation(s)
- Huaze Xu
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China
| | - Jianpo Su
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China
| | - Jian Qin
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China
| | - Ming Li
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China
| | - Ling-Li Zeng
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China
| | - Dewen Hu
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China
| | - Hui Shen
- College of Artificial Intelligence, National University of Defense Technology Changsha, Hunan, 410073, China.
| |
Collapse
|
28
|
Moraczewski D, Chen G, Redcay E. Inter-subject synchrony as an index of functional specialization in early childhood. Sci Rep 2018; 8:2252. [PMID: 29396415 PMCID: PMC5797124 DOI: 10.1038/s41598-018-20600-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Accepted: 01/22/2018] [Indexed: 12/11/2022] Open
Abstract
Early childhood is a time of significant change within multiple cognitive domains including social cognition, memory, executive function, and language; however, the corresponding neural changes remain poorly understood. This is likely due to the difficulty in acquiring artifact-free functional MRI data during complex task-based or unconstrained resting-state experiments in young children. In addition, task-based and resting state experiments may not capture dynamic real-world processing. Here we overcome both of these challenges through use of naturalistic viewing (i.e., passively watching a movie in the scanner) combined with inter-subject neural synchrony to examine functional specialization within 4- and 6-year old children. Using a novel and stringent crossed random effect statistical analysis, we find that children show more variable patterns of activation compared to adults, particularly within regions of the default mode network (DMN). In addition, we found partial evidence that child-to-adult synchrony increased as a function of age within a DMN region: the temporoparietal junction. Our results suggest age-related differences in functional brain organization within a cross-sectional sample during an ecologically valid context and demonstrate that neural synchrony during naturalistic viewing fMRI can be used to examine functional specialization during early childhood - a time when neural and cognitive systems are in flux.
Collapse
Affiliation(s)
- Dustin Moraczewski
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, 20742, USA.
- Computation and Mathematics for Biological Networks, University of Maryland, College Park, MD, 20742, USA.
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA.
| | - Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | - Elizabeth Redcay
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, 20742, USA
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA
| |
Collapse
|
29
|
Chen Z, Calhoun V. Effect of Spatial Smoothing on Task fMRI ICA and Functional Connectivity. Front Neurosci 2018; 12:15. [PMID: 29456485 PMCID: PMC5801305 DOI: 10.3389/fnins.2018.00015] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 01/10/2018] [Indexed: 12/24/2022] Open
Abstract
Spatial smoothing is a widely used preprocessing step in functional magnetic resonance imaging (fMRI) data analysis. In this work, we report on the spatial smoothing effect on task-evoked fMRI brain functional mapping and functional connectivity. Initially, we decomposed the task fMRI data into a collection of components or networks by independent component analysis (ICA). The designed task paradigm helps identify task-modulated ICA components (highly correlated with the task stimuli). For the ICA-extracted primary task component, we then measured the task activation volume at the task response foci. We used the task timecourse (designed) as a reference to order the ICA components according to the task correlations of the ICA timecourses. With the re-ordered ICA components, we calculated the inter-component function connectivity (FC) matrix (correlations among the ICA timecourses). By repeating the spatial smoothing of fMRI data with a Gaussian smoothing kernel with a full width at half maximum (FWHM) of {1, 3, 6, 9, 12, 15, 20, 25, 30, 35} mm, we measured the spatial smoothing effects. Our results show spatial smoothing reveals the following effects: (1) It decreases the task extraction performance of single-subject ICA more than that of multi-subject ICA; (2) It increases the task volume of multi-subject ICA more than that of single-subject ICA; (3) It strengthens the functional connectivity of single-subject ICA more than that of multi-subject ICA; and (4) It impacts the positive-negative imbalance of single-subject ICA more than that of multi-subject ICA. Our experimental results suggest a 2~3 voxel FWHM spatial smoothing for single-subject ICA in achieving an optimal balance of functional connectivity, and a wide range (2~5 voxels) of FWHM for multi-subject ICA.
Collapse
Affiliation(s)
- Zikuan Chen
- The Mind Research Network and LBERI, Albuquerque, NM, United States
| | - Vince Calhoun
- The Mind Research Network and LBERI, Albuquerque, NM, United States.,Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States
| |
Collapse
|
30
|
Rowland SC, Hartley DEH, Wiggins IM. Listening in Naturalistic Scenes: What Can Functional Near-Infrared Spectroscopy and Intersubject Correlation Analysis Tell Us About the Underlying Brain Activity? Trends Hear 2018; 22:2331216518804116. [PMID: 30345888 PMCID: PMC6198387 DOI: 10.1177/2331216518804116] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 08/17/2018] [Accepted: 09/06/2018] [Indexed: 12/24/2022] Open
Abstract
Listening to speech in the noisy conditions of everyday life can be effortful, reflecting the increased cognitive workload involved in extracting meaning from a degraded acoustic signal. Studying the underlying neural processes has the potential to provide mechanistic insight into why listening is effortful under certain conditions. In a move toward studying listening effort under ecologically relevant conditions, we used the silent and flexible neuroimaging technique functional near-infrared spectroscopy (fNIRS) to examine brain activity during attentive listening to speech in naturalistic scenes. Thirty normally hearing participants listened to a series of narratives continuously varying in acoustic difficulty while undergoing fNIRS imaging. Participants then listened to another set of closely matched narratives and rated perceived effort and intelligibility for each scene. As expected, self-reported effort generally increased with worsening signal-to-noise ratio. After controlling for better-ear signal-to-noise ratio, perceived effort was greater in scenes that contained competing speech than in those that did not, potentially reflecting an additional cognitive cost of overcoming informational masking. We analyzed the fNIRS data using intersubject correlation, a data-driven approach suitable for analyzing data collected under naturalistic conditions. Significant intersubject correlation was seen in the bilateral auditory cortices and in a range of channels across the prefrontal cortex. The involvement of prefrontal regions is consistent with the notion that higher order cognitive processes are engaged during attentive listening to speech in complex real-world conditions. However, further research is needed to elucidate the relationship between perceived listening effort and activity in these extended cortical networks.
Collapse
Affiliation(s)
- Stephen C. Rowland
- National Institute for Health Research Nottingham Biomedical Research Centre, UK
- Hearing Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, UK
| | - Douglas E. H. Hartley
- National Institute for Health Research Nottingham Biomedical Research Centre, UK
- Hearing Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, UK
- Medical Research Council Institute of Hearing Research, School of Medicine, University of Nottingham, UK
- Nottingham University Hospitals NHS Trust, Queens Medical Centre, UK
| | - Ian M. Wiggins
- National Institute for Health Research Nottingham Biomedical Research Centre, UK
- Hearing Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, UK
- Medical Research Council Institute of Hearing Research, School of Medicine, University of Nottingham, UK
| |
Collapse
|
31
|
Liu P, Calhoun V, Chen Z. Functional overestimation due to spatial smoothing of fMRI data. J Neurosci Methods 2017; 291:1-12. [DOI: 10.1016/j.jneumeth.2017.08.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Revised: 08/03/2017] [Accepted: 08/03/2017] [Indexed: 10/19/2022]
|
32
|
Alakörkkö T, Saarimäki H, Glerean E, Saramäki J, Korhonen O. Effects of spatial smoothing on functional brain networks. Eur J Neurosci 2017; 46:2471-2480. [PMID: 28922510 PMCID: PMC5698731 DOI: 10.1111/ejn.13717] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 08/22/2017] [Accepted: 09/13/2017] [Indexed: 12/19/2022]
Abstract
Graph-theoretical methods have rapidly become a standard tool in studies of the structure and function of the human brain. Whereas the structural connectome can be fairly straightforwardly mapped onto a complex network, there are more degrees of freedom in constructing networks that represent functional connections between brain areas. For functional magnetic resonance imaging (fMRI) data, such networks are typically built by aggregating the blood-oxygen-level dependent signal time series of voxels into larger entities (such as Regions of Interest in some brain atlas) and determining their connection strengths from some measure of time-series correlations. Although it is evident that the outcome must be affected by how the voxel-level time series are treated at the preprocessing stage, there is a lack of systematic studies of the effects of preprocessing on network structure. Here, we focus on the effects of spatial smoothing, a standard preprocessing method for fMRI. We apply various levels of spatial smoothing to resting-state fMRI data and measure the changes induced in functional networks. We show that the level of spatial smoothing clearly affects the degrees and other centrality measures of functional network nodes; these changes are non-uniform, systematic, and depend on the geometry of the brain. The composition of the largest connected network component is also affected in a way that artificially increases the similarity of the networks of different subjects. Our conclusion is that wherever possible, spatial smoothing should be avoided when preprocessing fMRI data for network analysis.
Collapse
Affiliation(s)
- Tuomas Alakörkkö
- Department of Computer ScienceSchool of ScienceAalto UniversityPO Box 15400FI‐00076AaltoEspooFinland
| | - Heini Saarimäki
- Department of Neuroscience and Biomedical EngineeringSchool of ScienceAalto UniversityEspooFinland
| | - Enrico Glerean
- Department of Neuroscience and Biomedical EngineeringSchool of ScienceAalto UniversityEspooFinland
- Turku PET CentreUniversity of TurkuTurkuFinland
| | - Jari Saramäki
- Department of Computer ScienceSchool of ScienceAalto UniversityPO Box 15400FI‐00076AaltoEspooFinland
| | - Onerva Korhonen
- Department of Computer ScienceSchool of ScienceAalto UniversityPO Box 15400FI‐00076AaltoEspooFinland
- Department of Neuroscience and Biomedical EngineeringSchool of ScienceAalto UniversityEspooFinland
| |
Collapse
|
33
|
Kauppi J, Pajula J, Niemi J, Hari R, Tohka J. Functional brain segmentation using inter-subject correlation in fMRI. Hum Brain Mapp 2017; 38:2643-2665. [PMID: 28295803 PMCID: PMC6867053 DOI: 10.1002/hbm.23549] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 01/27/2017] [Accepted: 02/15/2017] [Indexed: 01/05/2023] Open
Abstract
The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Jukka‐Pekka Kauppi
- Department of Mathematical Information TechnologyUniversity of JyväskyläJyväskyläFinland
- Department of Computer Science and HIITUniversity of HelsinkiHelsinkiFinland
| | - Juha Pajula
- Department of Signal ProcessingTampere University of TechnologyTampereFinland
- VTT Technical Research Centre of FinlandTampereFinland
| | - Jari Niemi
- Department of Signal ProcessingTampere University of TechnologyTampereFinland
| | - Riitta Hari
- Department of ArtAalto UniversityHelsinkiFinland
| | - Jussi Tohka
- AI Virtanen Institute for Molecular Sciences, University of Eastern FinlandKuopioFinland
| |
Collapse
|
34
|
Chen G, Shin YW, Taylor PA, Glen DR, Reynolds RC, Israel RB, Cox RW. Untangling the relatedness among correlations, part I: Nonparametric approaches to inter-subject correlation analysis at the group level. Neuroimage 2016; 142:248-259. [PMID: 27195792 DOI: 10.1016/j.neuroimage.2016.05.023] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Revised: 04/08/2016] [Accepted: 05/05/2016] [Indexed: 02/02/2023] Open
Abstract
FMRI data acquisition under naturalistic and continuous stimuli (e.g., watching a video or listening to music) has become popular recently due to the fact that it entails less manipulation and more realistic/complex contexts involved in the task, compared to the conventional task-based experimental designs. The synchronization or response similarities among subjects are typically measured through inter-subject correlation (ISC) between any pair of subjects. At the group level, summarizing the collection of ISC values is complicated by their intercorrelations, which necessarily lead to the violation of independence assumed in typical parametric approaches such as Student's t-test. Nonparametric methods, such as bootstrapping and permutation testing, have previously been adopted for testing purposes by resampling the time series of each subject, but the quantitative validity of these specific approaches in terms of controllability of false positive rate (FPR) has never been explored before. Here we survey the methods of ISC group analysis that have been employed in the literature, and discuss the issues involved in those methods. We then propose less computationally intensive nonparametric methods that can be performed at the group level (for both one- and two-sample analyses), as compared to the popular method of circularly shifting the EPI time series at the individual level. As part of the new approaches, subject-wise (SW) resampling is adopted instead of element-wise (EW) resampling, so that exchangeability and independence assumptions are satisfied, and the patterned correlation structure among the ISC values can be more accurately captured. We examine the FPR controllability and power achievement of all the methods through simulations, as well as their performance when applied to a real experimental dataset.
Collapse
Affiliation(s)
- Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA.
| | - Yong-Wook Shin
- University of Ulsan College of Medicine, Department of Psychiatry, Asan Medical Center, South Korea.
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
| | - Daniel R Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
| | - Robert B Israel
- Mathematics Department, The University of British Columbia, Canada
| | - Robert W Cox
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
| |
Collapse
|
35
|
How Many Is Enough? Effect of Sample Size in Inter-Subject Correlation Analysis of fMRI. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2016; 2016:2094601. [PMID: 26884746 PMCID: PMC4738700 DOI: 10.1155/2016/2094601] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Revised: 12/09/2015] [Accepted: 12/14/2015] [Indexed: 11/17/2022]
Abstract
Inter-subject correlation (ISC) is a widely used method for analyzing functional magnetic resonance imaging (fMRI) data acquired during naturalistic stimuli. A challenge in ISC analysis is to define the required sample size in the way that the results are reliable. We studied the effect of the sample size on the reliability of ISC analysis and additionally addressed the following question: How many subjects are needed for the ISC statistics to converge to the ISC statistics obtained using a large sample? The study was realized using a large block design data set of 130 subjects. We performed a split-half resampling based analysis repeatedly sampling two nonoverlapping subsets of 10–65 subjects and comparing the ISC maps between the independent subject sets. Our findings suggested that with 20 subjects, on average, the ISC statistics had converged close to a large sample ISC statistic with 130 subjects. However, the split-half reliability of unthresholded and thresholded ISC maps improved notably when the number of subjects was increased from 20 to 30 or more.
Collapse
|