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Shao X, Krieger-Redwood K, Zhang M, Hoffman P, Lanzoni L, Leech R, Smallwood J, Jefferies E. Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition. J Neurosci 2024; 44:e1907232024. [PMID: 38589231 PMCID: PMC11097276 DOI: 10.1523/jneurosci.1907-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 03/05/2024] [Accepted: 04/03/2024] [Indexed: 04/10/2024] Open
Abstract
The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.
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Affiliation(s)
- Ximing Shao
- Department of Psychology, University of York, York, YO10 5DD, United Kingdom
| | | | - Meichao Zhang
- Department of Psychology, University of York, York, YO10 5DD, United Kingdom
- CAS Key Laboratory of Behavioural Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Paul Hoffman
- School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom
| | - Lucilla Lanzoni
- Department of Psychology, University of York, York, YO10 5DD, United Kingdom
| | - Robert Leech
- Centre for Neuroimaging Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 9RT, United Kingdom
| | - Jonathan Smallwood
- Department of Psychology, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Elizabeth Jefferies
- Department of Psychology, University of York, York, YO10 5DD, United Kingdom
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2
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Cruces RR, Royer J, Herholz P, Larivière S, Vos de Wael R, Paquola C, Benkarim O, Park BY, Degré-Pelletier J, Nelson MC, DeKraker J, Leppert IR, Tardif C, Poline JB, Concha L, Bernhardt BC. Micapipe: A pipeline for multimodal neuroimaging and connectome analysis. Neuroimage 2022; 263:119612. [PMID: 36070839 PMCID: PMC10697132 DOI: 10.1016/j.neuroimage.2022.119612] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 08/20/2022] [Accepted: 09/03/2022] [Indexed: 11/25/2022] Open
Abstract
Multimodal magnetic resonance imaging (MRI) has accelerated human neuroscience by fostering the analysis of brain microstructure, geometry, function, and connectivity across multiple scales and in living brains. The richness and complexity of multimodal neuroimaging, however, demands processing methods to integrate information across modalities and to consolidate findings across different spatial scales. Here, we present micapipe, an open processing pipeline for multimodal MRI datasets. Based on BIDS-conform input data, micapipe can generate i) structural connectomes derived from diffusion tractography, ii) functional connectomes derived from resting-state signal correlations, iii) geodesic distance matrices that quantify cortico-cortical proximity, and iv) microstructural profile covariance matrices that assess inter-regional similarity in cortical myelin proxies. The above matrices can be automatically generated across established 18 cortical parcellations (100-1000 parcels), in addition to subcortical and cerebellar parcellations, allowing researchers to replicate findings easily across different spatial scales. Results are represented on three different surface spaces (native, conte69, fsaverage5), and outputs are BIDS-conform. Processed outputs can be quality controlled at the individual and group level. micapipe was tested on several datasets and is available at https://github.com/MICA-MNI/micapipe, documented at https://micapipe.readthedocs.io/, and containerized as a BIDS App http://bids-apps.neuroimaging.io/apps/. We hope that micapipe will foster robust and integrative studies of human brain microstructure, morphology, function, cand connectivity.
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Affiliation(s)
- Raúl R Cruces
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.
| | - Peer Herholz
- NeuroDataScience - ORIGAMI lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada; Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany
| | - Oualid Benkarim
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada; Department of Data Science, Inha University, Incheon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Janie Degré-Pelletier
- Labo IDEA, Département de Psychologie, Université du Québec à Montréal, Montréal, Québec, Canada
| | - Mark C Nelson
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Christine Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Jean-Baptiste Poline
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Luis Concha
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.
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Enguix V, Kenley J, Luck D, Cohen-Adad J, Lodygensky GA. NeoRS: A Neonatal Resting State fMRI Data Preprocessing Pipeline. Front Neuroinform 2022; 16:843114. [PMID: 35784189 PMCID: PMC9247272 DOI: 10.3389/fninf.2022.843114] [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: 12/24/2021] [Accepted: 05/27/2022] [Indexed: 11/20/2022] Open
Abstract
Resting state functional MRI (rsfMRI) has been shown to be a promising tool to study intrinsic brain functional connectivity and assess its integrity in cerebral development. In neonates, where functional MRI is limited to very few paradigms, rsfMRI was shown to be a relevant tool to explore regional interactions of brain networks. However, to identify the resting state networks, data needs to be carefully processed to reduce artifacts compromising the interpretation of results. Because of the non-collaborative nature of the neonates, the differences in brain size and the reversed contrast compared to adults due to myelination, neonates can’t be processed with the existing adult pipelines, as they are not adapted. Therefore, we developed NeoRS, a rsfMRI pipeline for neonates. The pipeline relies on popular neuroimaging tools (FSL, AFNI, and SPM) and is optimized for the neonatal brain. The main processing steps include image registration to an atlas, skull stripping, tissue segmentation, slice timing and head motion correction and regression of confounds which compromise functional data interpretation. To address the specificity of neonatal brain imaging, particular attention was given to registration including neonatal atlas type and parameters, such as brain size variations, and contrast differences compared to adults. Furthermore, head motion was scrutinized, and motion management optimized, as it is a major issue when processing neonatal rsfMRI data. The pipeline includes quality control using visual assessment checkpoints. To assess the effectiveness of NeoRS processing steps we used the neonatal data from the Baby Connectome Project dataset including a total of 10 neonates. NeoRS was designed to work on both multi-band and single-band acquisitions and is applicable on smaller datasets. NeoRS also includes popular functional connectivity analysis features such as seed-to-seed or seed-to-voxel correlations. Language, default mode, dorsal attention, visual, ventral attention, motor and fronto-parietal networks were evaluated. Topology found the different analyzed networks were in agreement with previously published studies in the neonate. NeoRS is coded in Matlab and allows parallel computing to reduce computational times; it is open-source and available on GitHub (https://github.com/venguix/NeoRS). NeoRS allows robust image processing of the neonatal rsfMRI data that can be readily customized to different datasets.
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Affiliation(s)
- Vicente Enguix
- Department of Pediatrics, CHU Sainte-Justine, University of Montreal, Montreal, QC, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Canadian Neonatal Brain Platform, Montreal, QC, Canada
- *Correspondence: Vicente Enguix,
| | - Jeanette Kenley
- Washington University School of Medicine, St. Louis, MO, United States
| | - David Luck
- Department of Pediatrics, CHU Sainte-Justine, University of Montreal, Montreal, QC, Canada
- Canadian Neonatal Brain Platform, Montreal, QC, Canada
| | - Julien Cohen-Adad
- Department of Pediatrics, CHU Sainte-Justine, University of Montreal, Montreal, QC, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, QC, Canada
- Mila – Quebec AI Institute, Montreal, QC, Canada
| | - Gregory Anton Lodygensky
- Department of Pediatrics, CHU Sainte-Justine, University of Montreal, Montreal, QC, Canada
- Canadian Neonatal Brain Platform, Montreal, QC, Canada
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Tonic pain alters functional connectivity of the descending pain modulatory network involving amygdala, periaqueductal gray, parabrachial nucleus and anterior cingulate cortex. Neuroimage 2022; 256:119278. [PMID: 35523367 PMCID: PMC9250649 DOI: 10.1016/j.neuroimage.2022.119278] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 04/07/2022] [Accepted: 05/02/2022] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION Resting state functional connectivity (FC) is widely used to assess functional brain alterations in patients with chronic pain. However, reports of FC accompanying tonic pain in pain-free persons are rare. A network we term the Descending Pain Modulatory Network (DPMN) is implicated in healthy and pathologic pain modulation. Here, we evaluate the effect of tonic pain on FC of specific nodes of this network: anterior cingulate cortex (ACC), amygdala (AMYG), periaqueductal gray (PAG), and parabrachial nuclei (PBN). METHODS In 50 pain-free participants (30F), we induced tonic pain using a capsaicin-heat pain model. functional MRI measured resting BOLD signal during pain-free rest with a 32°C thermode and then tonic pain where participants experienced a previously warm temperature combined with capsaicin. We evaluated FC from ACC, AMYG, PAG, and PBN with correlation of self-report pain intensity during both states. We hypothesized tonic pain would diminish FC dyads within the DPMN. RESULTS Of all hypothesized FC dyads, only PAG and subgenual ACC was weakly altered during pain (F=3.34; p=0.074; pain-free>pain d=0.25). After pain induction sACC-PAG FC became positively correlated with pain intensity (R=0.38; t=2.81; p=0.007). Right PBN-PAG FC during pain-free rest positively correlated with subsequently experienced pain (R=0.44; t=3.43; p=0.001). During pain, this connection's FC was diminished (paired t=-3.17; p=0.0026). In whole-brain analyses, during pain-free rest, FC between left AMYG and right superior parietal lobule and caudate nucleus were positively correlated with subsequent pain. During pain, FC between left AMYG and right inferior temporal gyrus negatively correlated with pain. Subsequent pain positively correlated with right AMYG FC with right claustrum; right primary visual cortex and right temporo-occipitoparietal junction Conclusion: We demonstrate sACC-PAG tonic pain FC positively correlates with experienced pain and resting right PBN-PAG FC correlates with subsequent pain and is diminished during tonic pain. Finally, we reveal PAG- and right AMYG-anchored networks which correlate with subsequently experienced pain intensity. Our findings suggest specific connectivity patterns within the DPMN at rest are associated with subsequently experienced pain and modulated by tonic pain. These nodes and their functional modulation may reveal new therapeutic targets for neuromodulation or biomarkers to guide interventions.
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Shao X, Mckeown B, Karapanagiotidis T, Vos de Wael R, Margulies DS, Bernhardt B, Smallwood J, Krieger-Redwood K, Jefferies E. Individual differences in gradients of intrinsic connectivity within the semantic network relate to distinct aspects of semantic cognition. Cortex 2022; 150:48-60. [DOI: 10.1016/j.cortex.2022.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 12/20/2021] [Accepted: 01/21/2022] [Indexed: 11/03/2022]
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Vos de Wael R, Royer J, Tavakol S, Wang Y, Paquola C, Benkarim O, Eichert N, Larivière S, Xu T, Misic B, Smallwood J, Valk SL, Bernhardt BC. Structural Connectivity Gradients of the Temporal Lobe Serve as Multiscale Axes of Brain Organization and Cortical Evolution. Cereb Cortex 2021; 31:5151-5164. [PMID: 34148082 PMCID: PMC8491677 DOI: 10.1093/cercor/bhab149] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The temporal lobe is implicated in higher cognitive processes and is one of the regions that underwent substantial reorganization during primate evolution. Its functions are instantiated, in part, by the complex layout of its structural connections. Here, we identified low-dimensional representations of structural connectivity variations in human temporal cortex and explored their microstructural underpinnings and associations to macroscale function. We identified three eigenmodes which described gradients in structural connectivity. These gradients reflected inter-regional variations in cortical microstructure derived from quantitative magnetic resonance imaging and postmortem histology. Gradient-informed models accurately predicted macroscale measures of temporal lobe function. Furthermore, the identified gradients aligned closely with established measures of functional reconfiguration and areal expansion between macaques and humans, highlighting their potential role in shaping temporal lobe function throughout primate evolution. Findings were replicated in several datasets. Our results provide robust evidence for three axes of structural connectivity in human temporal cortex with consistent microstructural underpinnings and contributions to large-scale brain network function.
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Affiliation(s)
- Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Jessica Royer
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Shahin Tavakol
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Yezhou Wang
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Oualid Benkarim
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Sara Larivière
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, NY 10022, USA
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | | | - Sofie L Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
| | - Boris C Bernhardt
- Address correspondence to Boris C. Bernhardt, McConnell Brain Imaging Centre, Montreal Neurological Institute (NW-256), McGill University, 3801 Rue University, Montréal, QC H3A2B4, Canada.
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Abnormal medial prefrontal cortex functional connectivity and its association with clinical symptoms in chronic low back pain. Pain 2020; 160:1308-1318. [PMID: 31107712 DOI: 10.1097/j.pain.0000000000001507] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Accumulating evidence has shown that complicated brain systems are involved in the development and maintenance of chronic low back pain (cLBP), but the association between brain functional changes and clinical outcomes remains unclear. Here, we used resting-state functional magnetic resonance imaging (fMRI) and multivariate pattern analysis to identify abnormal functional connectivity (FC) between the default mode, sensorimotor, salience, and central executive brain networks in cLBP and tested whether abnormal FCs are related to pain and comorbid symptoms. Fifty cLBP patients and 44 matched healthy controls (HCs) underwent an fMRI scan, from which brain networks were identified by independent component analysis. Multivariate pattern analysis, graph theory approaches, and correlation analyses were applied to find abnormal FCs that were associated with clinical symptoms. Findings were validated on a second cohort of 30 cLBP patients and 30 matched HCs. Results showed that the medial prefrontal cortex/rostral anterior cingulate cortex had abnormal FCs with brain regions within the default mode network and with other brain networks in cLBP patients. These altered FCs were also correlated with pain duration, pain severity, and pain interference. Finally, we found that resting-state FC could discriminate cLBP patients from HCs with 91% accuracy in the first cohort and 78% accuracy in the validation cohort. Our findings suggest that the medial prefrontal cortex/rostral anterior cingulate cortex may be an important hub for linking the default mode network with the other 3 networks in cLBP patients. Elucidating the altered FCs and their association with clinical outcomes will enhance our understanding of the pathophysiology of cLBP and may facilitate the development of pain management approaches.
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Noble S, Scheinost D, Constable RT. A decade of test-retest reliability of functional connectivity: A systematic review and meta-analysis. Neuroimage 2019; 203:116157. [PMID: 31494250 PMCID: PMC6907736 DOI: 10.1016/j.neuroimage.2019.116157] [Citation(s) in RCA: 276] [Impact Index Per Article: 55.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 08/30/2019] [Accepted: 09/02/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Once considered mere noise, fMRI-based functional connectivity has become a major neuroscience tool in part due to early studies demonstrating its reliability. These fundamental studies revealed only the tip of the iceberg; over the past decade, many test-retest reliability studies have continued to add nuance to our understanding of this complex topic. A summary of these diverse and at times contradictory perspectives is needed. OBJECTIVES We aimed to summarize the existing knowledge regarding test-retest reliability of functional connectivity at the most basic unit of analysis: the individual edge level. This entailed (1) a meta-analytic estimate of reliability and (2) a review of factors influencing reliability. METHODS A search of Scopus was conducted to identify studies that estimated edge-level test-retest reliability. To facilitate comparisons across studies, eligibility was restricted to studies measuring reliability via the intraclass correlation coefficient (ICC). The meta-analysis included a random effects pooled estimate of mean edge-level ICC, with studies nested within datasets. The review included a narrative summary of factors influencing edge-level ICC. RESULTS From an initial pool of 212 studies, 44 studies were identified for the qualitative review and 25 studies for quantitative meta-analysis. On average, individual edges exhibited a "poor" ICC of 0.29 (95% CI = 0.23 to 0.36). The most reliable measurements tended to involve: (1) stronger, within-network, cortical edges, (2) eyes open, awake, and active recordings, (3) more within-subject data, (4) shorter test-retest intervals, (5) no artifact correction (likely due in part to reliable artifact), and (6) full correlation-based connectivity with shrinkage. CONCLUSION This study represents the first meta-analysis and systematic review investigating test-retest reliability of edge-level functional connectivity. Key findings suggest there is room for improvement, but care should be taken to avoid promoting reliability at the expense of validity. By pooling existing knowledge regarding this key facet of accuracy, this study supports broader efforts to improve inferences in the field.
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Affiliation(s)
- Stephanie Noble
- Interdepartmental Neuroscience Program, Yale University, USA.
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale University, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, USA; Department of Statistics and Data Science, Yale University, USA; Child Study Center, Yale School of Medicine, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale University, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, USA; Department of Neurosurgery, Yale School of Medicine, USA
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Paquola C, Vos De Wael R, Wagstyl K, Bethlehem RAI, Hong SJ, Seidlitz J, Bullmore ET, Evans AC, Misic B, Margulies DS, Smallwood J, Bernhardt BC. Microstructural and functional gradients are increasingly dissociated in transmodal cortices. PLoS Biol 2019; 17:e3000284. [PMID: 31107870 PMCID: PMC6544318 DOI: 10.1371/journal.pbio.3000284] [Citation(s) in RCA: 218] [Impact Index Per Article: 43.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 05/31/2019] [Accepted: 05/08/2019] [Indexed: 01/10/2023] Open
Abstract
While the role of cortical microstructure in organising neural function is well established, it remains unclear how structural constraints can give rise to more flexible elements of cognition. While nonhuman primate research has demonstrated a close structure-function correspondence, the relationship between microstructure and function remains poorly understood in humans, in part because of the reliance on post mortem analyses, which cannot be directly related to functional data. To overcome this barrier, we developed a novel approach to model the similarity of microstructural profiles sampled in the direction of cortical columns. Our approach was initially formulated based on an ultra-high-resolution 3D histological reconstruction of an entire human brain and then translated to myelin-sensitive magnetic resonance imaging (MRI) data in a large cohort of healthy adults. This novel method identified a system-level gradient of microstructural differentiation traversing from primary sensory to limbic regions that followed shifts in laminar differentiation and cytoarchitectural complexity. Importantly, while microstructural and functional gradients described a similar hierarchy, they became increasingly dissociated in transmodal default mode and fronto-parietal networks. Meta-analytic decoding of these topographic dissociations highlighted involvement in higher-level aspects of cognition, such as cognitive control and social cognition. Our findings demonstrate a relative decoupling of macroscale functional from microstructural gradients in transmodal regions, which likely contributes to the flexible role these regions play in human cognition.
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Affiliation(s)
- Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Reinder Vos De Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Konrad Wagstyl
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
| | - Richard A. I. Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Seok-Jun Hong
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, Maryland, United States of America
- Brain Mapping Unit, University of Cambridge, Department of Psychiatry, Cambridge, United Kingdom
| | - Edward T. Bullmore
- Brain Mapping Unit, University of Cambridge, Department of Psychiatry, Cambridge, United Kingdom
| | - Alan C. Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | | | | | - Boris C. Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
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Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain. Neural Plast 2018; 2018:6120925. [PMID: 30008742 PMCID: PMC6020504 DOI: 10.1155/2018/6120925] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 02/20/2018] [Accepted: 04/03/2018] [Indexed: 02/02/2023] Open
Abstract
Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMRglc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMRglc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMRglc alterations compared to control were detected in all conditions except in congenitally blind where regional CMRglc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMRglc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMRglc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMRglc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMRglc data in health and disease.
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Johnson FK, Delpech JC, Thompson GJ, Wei L, Hao J, Herman P, Hyder F, Kaffman A. Amygdala hyper-connectivity in a mouse model of unpredictable early life stress. Transl Psychiatry 2018; 8:49. [PMID: 29463821 PMCID: PMC5820270 DOI: 10.1038/s41398-018-0092-z] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 12/06/2017] [Accepted: 12/13/2017] [Indexed: 01/09/2023] Open
Abstract
Childhood maltreatment is associated with a wide range of psychopathologies including anxiety that emerge in childhood and in many cases persist in adulthood. Increased amygdala activation in response to threat and abnormal amygdala connectivity with frontolimbic brain regions, such as the hippocampus and the prefrontal cortex, are some of the most consistent findings seen in individuals exposed to childhood maltreatment. The underlying mechanisms responsible for these changes are difficult to study in humans but can be elucidated using animal models of early-life stress. Such studies are especially powerful in the mouse where precise control of the genetic background and the stress paradigm can be coupled with resting-state fMRI (rsfMRI) to map abnormal connectivity in circuits that regulate anxiety. To address this issue we first compared the effects of two models of early-life stress, limited bedding (LB) and unpredictable postnatal stress (UPS), on anxiety-like behavior in juvenile and adult mice. We found that UPS, but not LB, causes a robust increase in anxiety in juvenile and adult male mice. Next, we used rsfMRI to compare frontolimbic connectivity in control and UPS adult male mice. We found increased amygdala-prefrontal cortex and amygdala-hippocampus connectivity in UPS. The strength of the amygdala-hippocampal and amygdala-prefrontal cortex connectivity was highly correlated with anxiety-like behavior in the open-field test and elevated plus maze. These findings are the first to link hyperconnectivity in frontolimbic circuits and increased anxiety in a mouse model of early-life stress, allowing for more mechanistic understanding of parallel findings in humans.
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Affiliation(s)
- Frances K Johnson
- Department of Psychiatry, Yale University School of Medicine, 300 George Street, Suite 901, New Haven, CT, 06511, USA
| | - Jean-Christophe Delpech
- Department of Psychiatry, Yale University School of Medicine, 300 George Street, Suite 901, New Haven, CT, 06511, USA
- Department of Newborn Medicine, Boston Children's Hospital, Harvard medical school, Boston, MA, 02115, USA
| | - Garth J Thompson
- Department of Radiology & Biomedical Imaging and Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA
- iHuman Institute, ShanghaiTech University, 393 Middle Huaxia Road, Ren Building, Room B204, Zhangjiang, Pudong, Shanghai, 201210, China
| | - Lan Wei
- Department of Psychiatry, Yale University School of Medicine, 300 George Street, Suite 901, New Haven, CT, 06511, USA
| | - Jin Hao
- Department of Psychiatry, Yale University School of Medicine, 300 George Street, Suite 901, New Haven, CT, 06511, USA
| | - Peter Herman
- Department of Radiology & Biomedical Imaging and Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA
| | - Fahmeed Hyder
- Department of Radiology & Biomedical Imaging and Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06519, USA
| | - Arie Kaffman
- Department of Psychiatry, Yale University School of Medicine, 300 George Street, Suite 901, New Haven, CT, 06511, USA.
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Thompson GJ, Sanganahalli BG, Baker KL, Herman P, Shepherd GM, Verhagen JV, Hyder F. Spontaneous activity forms a foundation for odor-evoked activation maps in the rat olfactory bulb. Neuroimage 2018; 172:586-596. [PMID: 29374582 DOI: 10.1016/j.neuroimage.2018.01.051] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 01/16/2018] [Accepted: 01/20/2018] [Indexed: 12/12/2022] Open
Abstract
Fluctuations in spontaneous activity have been observed by many neuroimaging techniques, but because these resting-state changes are not evoked by stimuli, it is difficult to determine how they relate to task-evoked activations. We conducted multi-modal neuroimaging scans of the rat olfactory bulb, both with and without odor, to examine interaction between spontaneous and evoked activities. Independent component analysis of spontaneous fluctuations revealed resting-state networks, and odor-evoked changes revealed activation maps. We constructed simulated activation maps using resting-state networks that were highly correlated to evoked activation maps. Simulated activation maps derived by intrinsic optical signal (IOS), which covers the dorsal portion of the glomerular sheet, significantly differentiated one odor's evoked activation map from the other two. To test the hypothesis that spontaneous activity of the entire glomerular sheet is relevant for representing odor-evoked activations, we used functional magnetic resonance imaging (fMRI) to map the entire glomerular sheet. In contrast to the IOS results, the fMRI-derived simulated activation maps significantly differentiated all three odors' evoked activation maps. Importantly, no evoked activation maps could be significantly differentiated using simulated activation maps produced using phase-randomized resting-state networks. Given that some highly organized resting-state networks did not correlate with any odors' evoked activation maps, we posit that these resting-state networks may characterize evoked activation maps associated with odors not studied. These results emphasize that fluctuations in spontaneous activity form a foundation for active processing, signifying the relevance of resting-state mapping to functional neuroimaging.
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Affiliation(s)
- Garth J Thompson
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Basavaraju G Sanganahalli
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA; Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA
| | - Keeley L Baker
- Department of Neuroscience, Yale University, New Haven, CT, USA; The John B. Pierce Laboratory, New Haven, CT USA
| | - Peter Herman
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA; Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA
| | | | - Justus V Verhagen
- Department of Neuroscience, Yale University, New Haven, CT, USA; The John B. Pierce Laboratory, New Haven, CT USA
| | - Fahmeed Hyder
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA; Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA; Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
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13
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Detection of synchronous brain activity in white matter tracts at rest and under functional loading. Proc Natl Acad Sci U S A 2017; 115:595-600. [PMID: 29282320 DOI: 10.1073/pnas.1711567115] [Citation(s) in RCA: 136] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Functional MRI based on blood oxygenation level-dependent (BOLD) contrast is well established as a neuroimaging technique for detecting neural activity in the cortex of the human brain. While detection and characterization of BOLD signals, as well as their electrophysiological and hemodynamic/metabolic origins, have been extensively studied in gray matter (GM), the detection and interpretation of BOLD signals in white matter (WM) remain controversial. We have previously observed that BOLD signals in a resting state reveal structure-specific anisotropic temporal correlations in WM and that external stimuli alter these correlations and permit visualization of task-specific fiber pathways, suggesting variations in WM BOLD signals are related to neural activity. In this study, we provide further strong evidence that BOLD signals in WM reflect neural activities both in a resting state and under functional loading. We demonstrate that BOLD signal waveforms in stimulus-relevant WM pathways are synchronous with the applied stimuli but with various degrees of time delay and that signals in WM pathways exhibit clear task specificity. Furthermore, resting-state signal fluctuations in WM tracts show significant correlations with specific parcellated GM volumes. These observations support the notion that neural activities are encoded in WM circuits similarly to cortical responses.
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