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Seghier ML. 7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery. Eur Radiol Exp 2024; 8:73. [PMID: 38945979 PMCID: PMC11214939 DOI: 10.1186/s41747-024-00472-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 04/22/2024] [Indexed: 07/02/2024] Open
Abstract
Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.
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Affiliation(s)
- Mohamed L Seghier
- Department of Biomedical Engineering and Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, UAE.
- Healtcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, UAE.
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2
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Waks M, Lagore RL, Auerbach E, Grant A, Sadeghi-Tarakameh A, DelaBarre L, Jungst S, Tavaf N, Lattanzi R, Giannakopoulos I, Moeller S, Wu X, Yacoub E, Vizioli L, Schmidt S, Metzger GJ, Eryaman Y, Adriany G, Uğurbil K. RF coil design strategies for improving SNR at the ultrahigh magnetic field of 10.5 Tesla. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595628. [PMID: 38826245 PMCID: PMC11142186 DOI: 10.1101/2024.05.23.595628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Purpose To develop multichannel transmit and receive arrays towards capturing the ultimate-intrinsic-SNR (uiSNR) at 10.5 Tesla (T) and to demonstrate the feasibility and potential of whole-brain, high-resolution human brain imaging at this high field strength. Methods A dual row 16-channel self-decoupled transmit (Tx) array was converted to a 16Tx/Rx transceiver using custom transmit/receive switches. A 64-channel receive-only (64Rx) array was built to fit into the 16Tx/Rx array. Electromagnetic modeling and experiments were employed to define safe operation limits of the resulting 16Tx/80Rx array and obtain FDA approval for human use. Results The 64Rx array alone captured approximately 50% of the central uiSNR at 10.5T while the identical 7T 64Rx array captured ∼76% of uiSNR at this lower field strength. The 16Tx/80Rx configuration brought the fraction of uiSNR captured at 10.5T to levels comparable to the performance of the 64Rx array at 7T. SNR data obtained at the two field strengths with these arrays displayed dependent increases over a large central region. Whole-brain high resolution T 2 * and T 1 weighted anatomical and gradient-recalled echo EPI BOLD fMRI images were obtained at 10.5T for the first time with such an advanced array, illustrating the promise of >10T fields in studying the human brain. Conclusion We demonstrated the ability to approach the uiSNR at 10.5T over the human brain with a novel, high channel count array, achieving large SNR gains over 7T, currently the most commonly employed ultrahigh field platform, and demonstrate high resolution and high contrast anatomical and functional imaging at 10.5T.
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3
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Williams JC, Tubiolo PN, Zheng ZJ, Silver-Frankel EB, Pham DT, Haubold NK, Abeykoon SK, Abi-Dargham A, Horga G, Van Snellenberg JX. Functional Localization of the Human Auditory and Visual Thalamus Using a Thalamic Localizer Functional Magnetic Resonance Imaging Task. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.28.591516. [PMID: 38746171 PMCID: PMC11092475 DOI: 10.1101/2024.04.28.591516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due in part to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmark their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.
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4
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Billot A, Kiran S. Disentangling neuroplasticity mechanisms in post-stroke language recovery. BRAIN AND LANGUAGE 2024; 251:105381. [PMID: 38401381 PMCID: PMC10981555 DOI: 10.1016/j.bandl.2024.105381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 11/28/2023] [Accepted: 01/12/2024] [Indexed: 02/26/2024]
Abstract
A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal of enhancing treatment outcomes. Subsequent to recent advances in neuroimaging techniques, we now have the ability to examine more closely how neural activity patterns change after a stroke. However, the way these neural activity changes relate to language impairments and language recovery is still debated. The aim of this review is to provide a theoretical framework to better investigate and interpret neuroplasticity mechanisms underlying language recovery in post-stroke aphasia. We detail two sets of neuroplasticity mechanisms observed at the synaptic level that may explain functional neuroimaging findings in post-stroke aphasia recovery at the network level: feedback-based homeostatic plasticity and associative Hebbian plasticity. In conjunction with these plasticity mechanisms, higher-order cognitive control processes dynamically modulate neural activity in other regions to meet communication demands, despite reduced neural resources. This work provides a network-level neurobiological framework for understanding neural changes observed in post-stroke aphasia and can be used to define guidelines for personalized treatment development.
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Affiliation(s)
- Anne Billot
- Center for Brain Recovery, Boston University, Boston, USA; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Swathi Kiran
- Center for Brain Recovery, Boston University, Boston, USA.
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5
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Luo Z, Yin E, Zeng LL, Shen H, Su J, Peng L, Yan Y, Hu D. Frequency-specific segregation and integration of human cerebral cortex: An intrinsic functional atlas. iScience 2024; 27:109206. [PMID: 38439977 PMCID: PMC10910261 DOI: 10.1016/j.isci.2024.109206] [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: 07/31/2023] [Revised: 11/24/2023] [Accepted: 02/07/2024] [Indexed: 03/06/2024] Open
Abstract
The cognitive and behavioral functions of the human brain are supported by its frequency multiplexing mechanism. However, there is limited understanding of the dynamics of the functional network topology. This study aims to investigate the frequency-specific topology of the functional human brain using 7T rs-fMRI data. Frequency-specific parcellations were first performed, revealing frequency-dependent dynamics within the frontoparietal control, parietal memory, and visual networks. An intrinsic functional atlas containing 456 parcels was proposed and validated using stereo-EEG. Graph theory analysis suggested that, in addition to the task-positive vs. task-negative organization observed in static networks, there was a cognitive control system additionally from a frequency perspective. The reproducibility and plausibility of the identified hub sets were confirmed through 3T fMRI analysis, and their artificial removal had distinct effects on network topology. These results indicate a more intricate and subtle dynamics of the functional human brain and emphasize the significance of accurate topography.
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Affiliation(s)
- Zhiguo Luo
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Erwei Yin
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Hui Shen
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Jianpo Su
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Limin Peng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Ye Yan
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
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6
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Eisenstein T, Furman-Haran E, Tal A. Early excitatory-inhibitory cortical modifications following skill learning are associated with motor memory consolidation and plasticity overnight. Nat Commun 2024; 15:906. [PMID: 38291029 PMCID: PMC10828487 DOI: 10.1038/s41467-024-44979-9] [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: 04/19/2023] [Accepted: 01/08/2024] [Indexed: 02/01/2024] Open
Abstract
Consolidation of motor memories is vital to offline enhancement of new motor skills and involves short and longer-term offline processes following learning. While emerging evidence link glutamate and GABA dynamics in the primary motor cortex (M1) to online motor skill practice, its relationship with offline consolidation processes in humans is unclear. Using two-day repeated measures of behavioral and multimodal neuroimaging data before and following motor sequence learning, we show that short-term glutamatergic and GABAergic responses in M1 within minutes after learning were associated with longer-term learning-induced functional, structural, and behavioral modifications overnight. Furthermore, Glutamatergic and GABAergic modifications were differentially associated with different facets of motor memory consolidation. Our results point to unique and distinct roles of Glutamate and GABA in motor memory consolidation processes in the human brain across timescales and mechanistic levels, tying short-term changes on the neurochemical level to overnight changes in macroscale structure, function, and behavior.
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Affiliation(s)
- Tamir Eisenstein
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.
| | - Edna Furman-Haran
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel
| | - Assaf Tal
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.
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7
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Haynes G, Muhammad F, Khan AF, Mohammadi E, Smith ZA, Ding L. The current state of spinal cord functional magnetic resonance imaging and its application in clinical research. J Neuroimaging 2023; 33:877-888. [PMID: 37740582 DOI: 10.1111/jon.13158] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/11/2023] [Indexed: 09/24/2023] Open
Abstract
Since its development, spinal cord functional magnetic resonance imaging (fMRI) has utilized various methodologies and stimulation protocols to develop a deeper understanding of a healthy human spinal cord that lays a foundation for its use in clinical research and practice. In this review, we conducted a comprehensive literature search on spinal cord fMRI studies and summarized the recent advancements and resulting scientific achievements of spinal cord fMRI in the following three aspects: the current state of spinal cord fMRI methodologies and stimulation protocols, knowledge about the healthy spinal cord's functions obtained via spinal cord fMRI, and fMRI's exemplary usage in spinal cord diseases and injuries. We conclude with a discussion that, while technical challenges exist, novel fMRI technologies for and new knowledge about the healthy human spinal cord have been established. Empowered by these developments, investigations of pathological and injury states within the spinal cord have become the next important direction of spinal cord fMRI. Recent clinical investigations into spinal cord pathologies, for example, fibromyalgia, multiple sclerosis, spinal cord injury, and cervical spondylotic myelopathy, have already provided deep insights into spinal cord impairments and the time course of impairment-caused changes. We expect that future spinal cord fMRI advancement and research development will further enhance our understanding of various spinal cord diseases and provide the foundation for evaluating existing and developing new treatment plans.
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Affiliation(s)
- Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Esmaeil Mohammadi
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, Oklahoma, USA
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8
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Bijsterbosch JD, Farahibozorg SR, Glasser MF, Essen DV, Snyder LH, Woolrich MW, Smith SM. Evaluating functional brain organization in individuals and identifying contributions to network overlap. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558809. [PMID: 37790508 PMCID: PMC10542549 DOI: 10.1101/2023.09.21.558809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Individual differences in the spatial organization of resting state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting state networks can be derived using high quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that network overlap is indicative of linear additive coupling. These results suggest that regions of network overlap concurrently process information from all contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.
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Affiliation(s)
- Janine D Bijsterbosch
- Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | | | - Matthew F Glasser
- Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - David Van Essen
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - Lawrence H Snyder
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
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9
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Xing XX, Gao X, Jiang C. Individual Variability of Human Cortical Spontaneous Activity by 3T/7T fMRI. Neuroscience 2023; 528:117-128. [PMID: 37544577 DOI: 10.1016/j.neuroscience.2023.07.032] [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: 09/10/2022] [Revised: 07/29/2023] [Accepted: 07/31/2023] [Indexed: 08/08/2023]
Abstract
Mapping variability in cortical spontaneous activity (CSA) is an essential goal of understanding various sources of dark brain energy in human neuroscience. CSA was traditionally characterized using resting-state functional MRI (rfMRI) at 1.5T or 3T magnets while recently with 7T-rfMRI. However, the utility and interpretability of 7T-rfMRI must first be established for its variability. By leveraging rfMRI data from the Human Connectome Project (HCP), we derived CSA metrics with 3T-rfMRI and 7T-rfMRI for the same 84 healthy participants (52 females). The 7T-rfMRI produces different CSA metrics at multiple spatial-scales and their variability from the 3T-rfMRI. These differences were spatially dependent and varied according to specific cortical organization. For the amplitude metric, 7T-rfMRI enhanced its spatial contrasts in the anterior cortex but weakened it in the posterior cortex. An opposite pattern was observed for the connectivity metrics. The reliability changes of these metrics were scale dependent, indicating enhanced reliability for connectivity but weakened reliability for amplitude by 7T-rfMRI. These effects were primarily located in the high-order associate cortex, parsing the corresponding changes in individual differences with respect to 7T-rfMRI: (1) higher connectivity variability between participants and the lower connectivity variability within individual participants, and (2) lower amplitude variability between participants and higher amplitude variability within participants. Our work, for the first time, demonstrated the variability of the human CSA across space, rfMRI settings/platforms, and individuals. We discussed the statistical implications of our findings on CSA-based experimental designs and reproducible neuroscience as well as their translational value for personalized applications.
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Affiliation(s)
- Xiu-Xia Xing
- Department of Applied Mathematics, College of Mathematics, Faculty of Science, Beijing University of Technology, Beijing 100124, China.
| | - Xiao Gao
- School of Psychology, Capital Normal University, Beijing 100048, China
| | - Chao Jiang
- Faculty of Psychology, Southwest University, Chongqing 400715, China
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10
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Wang J, Gao X, Xiang Z, Sun F, Yang Y. Evaluation of consciousness rehabilitation via neuroimaging methods. Front Hum Neurosci 2023; 17:1233499. [PMID: 37780959 PMCID: PMC10537959 DOI: 10.3389/fnhum.2023.1233499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/30/2023] [Indexed: 10/03/2023] Open
Abstract
Accurate evaluation of patients with disorders of consciousness (DoC) is crucial for personalized treatment. However, misdiagnosis remains a serious issue. Neuroimaging methods could observe the conscious activity in patients who have no evidence of consciousness in behavior, and provide objective and quantitative indexes to assist doctors in their diagnosis. In the review, we discussed the current research based on the evaluation of consciousness rehabilitation after DoC using EEG, fMRI, PET, and fNIRS, as well as the advantages and limitations of each method. Nowadays single-modal neuroimaging can no longer meet the researchers` demand. Considering both spatial and temporal resolution, recent studies have attempted to focus on the multi-modal method which can enhance the capability of neuroimaging methods in the evaluation of DoC. As neuroimaging devices become wireless, integrated, and portable, multi-modal neuroimaging methods will drive new advancements in brain science research.
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Affiliation(s)
| | | | | | - Fangfang Sun
- College of Automation, Hangzhou Dianzi University, Hangzhou, China
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11
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Kulkarni M, Kent JS, Park K, Guell X, Anteraper S. Resting-state functional connectivity-based parcellation of the human dentate nucleus: new findings and clinical relevance. Brain Struct Funct 2023; 228:1799-1810. [PMID: 37439862 DOI: 10.1007/s00429-023-02665-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/11/2023] [Indexed: 07/14/2023]
Abstract
For years, the cerebellum was left out of functional magnetic resonance imaging (fMRI) studies due to technological limitations. The advent of novel data acquisition and reconstruction strategies (e.g., whole-brain simultaneous multi-slice imaging) employing multi-channel array coils has overcome such limitations, ushering unprecedented improvements in temporal signal-to-noise ratio and spatiotemporal resolution. Here, we aim to provide a brief report on the deep cerebellar nuclei, specifically focusing on the dentate nuclei, the primary output nuclei, situated within both cognitive and motor cerebello-cerebral circuits. We highlight the importance of functional parcellation in refining our understanding of broad resting-state functional connectivity (RSFC) in both health and disease. First, we review work relevant to the functional topography of the dentate nuclei, including recent advances in functional parcellation. Next, we review RSFC studies using the dentate nuclei as seed regions of interest in neurological and psychiatric populations and discuss the potential benefits of applying functionally defined subdivisions. Finally, we discuss recent technological advances and underscore ultrahigh-field neuroimaging as a tool to potentiate functionally parcellated RSFC analyses in clinical populations.
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Affiliation(s)
- Maitreyee Kulkarni
- Department of Psychology, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, USA
| | - Jerillyn S Kent
- Department of Psychology, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, USA
| | - Katie Park
- University of Illinois Urbana-Champaign, Champaign, IL, USA
| | - Xavier Guell
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sheeba Anteraper
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, United States.
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12
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Veréb D, Mijalkov M, Canal-Garcia A, Chang YW, Gomez-Ruiz E, Gerboles BZ, Kivipelto M, Svenningsson P, Zetterberg H, Volpe G, Betts M, Jacobs HIL, Pereira JB. Age-related differences in the functional topography of the locus coeruleus and their implications for cognitive and affective functions. eLife 2023; 12:RP87188. [PMID: 37650882 PMCID: PMC10471162 DOI: 10.7554/elife.87188] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023] Open
Abstract
The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg UniversityGoteborgSweden
| | | | - Blanca Zufiria Gerboles
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- University of Eastern FinlandKuopioFinland
| | - Per Svenningsson
- University of Eastern FinlandKuopioFinland
- Department of Clinical Neuroscience, Karolinska InstitutetStockholmSweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative Disease, UCL Institute of NeurologyLondonUnited Kingdom
- UK Dementia Research Institute at UCLLondonUnited Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water BayHong KongChina
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-MadisonMadisonUnited States
| | - Giovanni Volpe
- Department of Physics, Goteborg UniversityGoteborgSweden
| | - Matthew Betts
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative Diseases (DZNE), Otto-von-Guericke University MagdeburgMagdeburgGermany
- Center for Behavioral Brain Sciences, University of MagdeburgMagdeburgGermany
| | - Heidi IL Jacobs
- Maastricht UniversityMaastrichtNetherlands
- Massachusetts General HospitalBostonUnited States
| | - Joana B Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund UniversityLundSweden
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13
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Giacometti C, Amiez C, Hadj-Bouziane F. Multiple routes of communication within the amygdala-mPFC network: A comparative approach in humans and macaques. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 5:100103. [PMID: 37601951 PMCID: PMC10432920 DOI: 10.1016/j.crneur.2023.100103] [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: 10/10/2022] [Revised: 06/14/2023] [Accepted: 07/15/2023] [Indexed: 08/22/2023] Open
Abstract
The network formed by the amygdala (AMG) and the medial Prefrontal Cortex (mPFC), at the interface between our internal and external environment, has been shown to support some important aspects of behavioral adaptation. Whether and how the anatomo-functional organization of this network evolved across primates remains unclear. Here, we compared AMG nuclei morphological characteristics and their functional connectivity with the mPFC in humans and macaques to identify potential homologies and differences between these species. Based on selected studies, we highlight two subsystems within the AMG-mPFC circuits, likely involved in distinct temporal dynamics of integration during behavioral adaptation. We also show that whereas the mPFC displays a large expansion but a preserved intrinsic anatomo-functional organization, the AMG displays a volume reduction and morphological changes related to specific nuclei. We discuss potential commonalities and differences in the dialogue between AMG nuclei and mPFC in humans and macaques based on available data.
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Affiliation(s)
- C. Giacometti
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - C. Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - F. Hadj-Bouziane
- Integrative Multisensory Perception Action & Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), University of Lyon 1, Lyon, France
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14
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Veréb D, Mijalkov M, Canal-Garcia A, Chang YW, Gomez-Ruis E, Gerboles BZ, Kivipelto M, Svenningsson P, Zetterberg H, Volpe G, Betts MJ, Jacobs H, Pereira JB. Age-related differences in the functional topography of the locus coeruleus: implications for cognitive and affective functions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.25.23286442. [PMID: 37333117 PMCID: PMC10274957 DOI: 10.1101/2023.02.25.23286442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging and whether it is associated with cognition and mood. Here we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years old (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg University, Goteborg, Sweden
| | | | - Blanca Zufiria Gerboles
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- University of Eastern Finland, Kuopio, Finland
| | - Per Svenningsson
- University of Eastern Finland, Kuopio, Finland
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Mathew J. Betts
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Sciences, University of Magdeburg, Magdeburg, Germany
| | - Heidi Jacobs
- Maastricht University, Maastricht, The Netherlands
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Joana B. Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
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15
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Lucas A, Cornblath EJ, Sinha N, Caciagli L, Hadar P, Tranquille A, Stein JM, Das S, Davis KA. Improved Seizure Onset-Zone Lateralization in Temporal Lobe Epilepsy using 7T Resting-State fMRI: A Direct Comparison with 3T. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.06.23291025. [PMID: 37333141 PMCID: PMC10275004 DOI: 10.1101/2023.06.06.23291025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Objective Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high-field strengths (≥7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI. Methods We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs-fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths. Results Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (pFDR=0.008) than at 3T (pFDR=0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism. Significance We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
| | | | | | | | - Peter Hadar
- Department of Neurology, Massachussets General Hospital (work conducted while at the University of Pennsylvania)
| | | | - Joel M Stein
- Department of Radiology, University of Pennsylvania
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16
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Wang H, Wang X, Wang Y, Zhang D, Yang Y, Zhou Y, Qiu B, Zhang P. White matter BOLD signals at 7 Tesla reveal visual field maps in optic radiation and vertical occipital fasciculus. Neuroimage 2023; 269:119916. [PMID: 36736638 DOI: 10.1016/j.neuroimage.2023.119916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/18/2023] [Accepted: 01/30/2023] [Indexed: 02/03/2023] Open
Abstract
There is growing evidence that blood-oxygen-level-dependent (BOLD) activity in the white matter (WM) can be detected by functional magnetic resonance imaging (fMRI). However, the functional relevance and significance of WM BOLD signals remain controversial. Here we investigated whether 7T BOLD fMRI can reveal fine-scale functional organizations of a WM bundle. Population receptive field (pRF) analyses of the 7T retinotopy dataset from the Human Connectome Project revealed clear contralateral retinotopic organizations of two visual WM bundles: the optic radiation (OR) and the vertical occipital fasciculus (VOF). The retinotopic maps of OR are highly consistent with post-mortem dissections and diffusion tractographies, while the VOF maps are compatible with the dorsal and ventral visual areas connected by the WM. Similar to the grey matter (GM) visual areas, both WM bundles show over-representations of the central visual field and increasing pRF size with eccentricity. Hemodynamic response functions of visual WM were slower and wider compared with those of GM areas. These findings clearly demonstrate that WM BOLD at 7 Tesla is closely coupled with neural activity related to axons, encoding highly specific information that can be used to characterize fine-scale functional organizations of a WM bundle.
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Affiliation(s)
- Huan Wang
- Hefei National Research Center for Physical Sciences at the Microscale, School of Life Science, University of Science and Technology of China, Hefei, Anhui 230027, China; State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaoxiao Wang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yanming Wang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Du Zhang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yan Yang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yifeng Zhou
- Hefei National Research Center for Physical Sciences at the Microscale, School of Life Science, University of Science and Technology of China, Hefei, Anhui 230027, China; State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
| | - Bensheng Qiu
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China.
| | - Peng Zhang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; School of Ophthalmology and Optometry and Eye hospital, and State Key Laboratory of Ophthalmology, Optometry and Vision Science, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China.; University of Chinese Academy of Sciences, Beijing 100049, China..
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17
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de Godoy LL, Studart-Neto A, de Paula DR, Green N, Halder A, Arantes P, Chaim KT, Moraes NC, Yassuda MS, Nitrini R, Dresler M, da Costa Leite C, Panovska-Griffiths J, Soddu A, Bisdas S. Phenotyping Superagers Using Resting-State fMRI. AJNR Am J Neuroradiol 2023; 44:424-433. [PMID: 36927760 PMCID: PMC10084893 DOI: 10.3174/ajnr.a7820] [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: 07/28/2022] [Accepted: 02/19/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND AND PURPOSE Superagers are defined as older adults with episodic memory performance similar or superior to that in middle-aged adults. This study aimed to investigate the key differences in discriminative networks and their main nodes between superagers and cognitively average elderly controls. In addition, we sought to explore differences in sensitivity in detecting these functional activities across the networks at 3T and 7T MR imaging fields. MATERIALS AND METHODS Fifty-five subjects 80 years of age or older were screened using a detailed neuropsychological protocol, and 31 participants, comprising 14 superagers and 17 cognitively average elderly controls, were included for analysis. Participants underwent resting-state-fMRI at 3T and 7T MR imaging. A prediction classification algorithm using a penalized regression model on the measurements of the network was used to calculate the probabilities of a healthy older adult being a superager. Additionally, ORs quantified the influence of each node across preselected networks. RESULTS The key networks that differentiated superagers and elderly controls were the default mode, salience, and language networks. The most discriminative nodes (ORs > 1) in superagers encompassed areas in the precuneus posterior cingulate cortex, prefrontal cortex, temporoparietal junction, temporal pole, extrastriate superior cortex, and insula. The prediction classification model for being a superager showed better performance using the 7T compared with 3T resting-state-fMRI data set. CONCLUSIONS Our findings suggest that the functional connectivity in the default mode, salience, and language networks can provide potential imaging biomarkers for predicting superagers. The 7T field holds promise for the most appropriate study setting to accurately detect the functional connectivity patterns in superagers.
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Affiliation(s)
- L L de Godoy
- From the Departments of Radiology and Oncology (L.L.d.G., P.A., K.T.C., C.d.C.L.)
- Lysholm Department of Neuroradiology (L.L.d.G., S.B.), The National Hospital of Neurology and Neurosurgery
| | - A Studart-Neto
- Neurology (A.S.-N., N.C.M., M.S.Y., R.N.), Hospital das Clinicas, Faculdade de Medicina da Universidade de Sao Paulo, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - D R de Paula
- Donders Institute for Brain Cognition and Behavior (D.R.d.P., M.D.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - N Green
- Department of Statistics (N.G.), University College London, London, UK
| | - A Halder
- Departments of Medical Biophysics (A.H.)
| | - P Arantes
- From the Departments of Radiology and Oncology (L.L.d.G., P.A., K.T.C., C.d.C.L.)
| | - K T Chaim
- From the Departments of Radiology and Oncology (L.L.d.G., P.A., K.T.C., C.d.C.L.)
| | - N C Moraes
- Neurology (A.S.-N., N.C.M., M.S.Y., R.N.), Hospital das Clinicas, Faculdade de Medicina da Universidade de Sao Paulo, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - M S Yassuda
- Neurology (A.S.-N., N.C.M., M.S.Y., R.N.), Hospital das Clinicas, Faculdade de Medicina da Universidade de Sao Paulo, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - R Nitrini
- Neurology (A.S.-N., N.C.M., M.S.Y., R.N.), Hospital das Clinicas, Faculdade de Medicina da Universidade de Sao Paulo, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - M Dresler
- Donders Institute for Brain Cognition and Behavior (D.R.d.P., M.D.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - C da Costa Leite
- From the Departments of Radiology and Oncology (L.L.d.G., P.A., K.T.C., C.d.C.L.)
| | - J Panovska-Griffiths
- The Big Data Institute and the Pandemic Sciences Institute (J.P.-G.)
- The Queen's College (J.P.-G.), University of Oxford, Oxford, UK
| | - A Soddu
- Physics and Astronomy (A.S.), University of Western Ontario, London, Ontario, Canada
| | - S Bisdas
- Lysholm Department of Neuroradiology (L.L.d.G., S.B.), The National Hospital of Neurology and Neurosurgery
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18
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Schallmo MP, Weldon KB, Kamath RS, Moser HR, Montoya SA, Killebrew KW, Demro C, Grant AN, Marjańska M, Sponheim SR, Olman CA. The Psychosis Human Connectome Project: Design and rationale for studies of visual neurophysiology. Neuroimage 2023; 272:120060. [PMID: 36997137 PMCID: PMC10153004 DOI: 10.1016/j.neuroimage.2023.120060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/01/2023] Open
Abstract
Visual perception is abnormal in psychotic disorders such as schizophrenia. In addition to hallucinations, laboratory tests show differences in fundamental visual processes including contrast sensitivity, center-surround interactions, and perceptual organization. A number of hypotheses have been proposed to explain visual dysfunction in psychotic disorders, including an imbalance between excitation and inhibition. However, the precise neural basis of abnormal visual perception in people with psychotic psychopathology (PwPP) remains unknown. Here, we describe the behavioral and 7 tesla MRI methods we used to interrogate visual neurophysiology in PwPP as part of the Psychosis Human Connectome Project (HCP). In addition to PwPP (n = 66) and healthy controls (n = 43), we also recruited first-degree biological relatives (n = 44) in order to examine the role of genetic liability for psychosis in visual perception. Our visual tasks were designed to assess fundamental visual processes in PwPP, whereas MR spectroscopy enabled us to examine neurochemistry, including excitatory and inhibitory markers. We show that it is feasible to collect high-quality data across multiple psychophysical, functional MRI, and MR spectroscopy experiments with a sizable number of participants at a single research site. These data, in addition to those from our previously described 3 tesla experiments, will be made publicly available in order to facilitate further investigations by other research groups. By combining visual neuroscience techniques and HCP brain imaging methods, our experiments offer new opportunities to investigate the neural basis of abnormal visual perception in PwPP.
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Affiliation(s)
- Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN.
| | - Kimberly B Weldon
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Rohit S Kamath
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Hannah R Moser
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Samantha A Montoya
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Kyle W Killebrew
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN; Department of Psychology, University of Minnesota, Minneapolis, MN
| | - Andrea N Grant
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Scott R Sponheim
- Veterans Affairs Medical Center, Minneapolis, MN; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Cheryl A Olman
- Department of Psychology, University of Minnesota, Minneapolis, MN; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
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19
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Seifert AC, Xu J. Impact of autocalibration method on accelerated EPI of the cervical spinal cord at 7 T. Magn Reson Med 2022; 88:2583-2591. [PMID: 36000559 PMCID: PMC9529816 DOI: 10.1002/mrm.29415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 07/14/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE The spinal cord contains sensorimotor neural circuits of scientific and clinical interest. However, spinal cord functional MRI (fMRI) is significantly more technically demanding than brain fMRI, due primarily to its proximity to the lungs. Accelerated echo-planar imaging (EPI) at 7 T is particularly vulnerable to k-space phase inconsistencies induced by motion or B0 fluctuation, during either autocalibration signal (ACS) or time-series acquisition. For 7 T brain fMRI, sensitivity to motion and B0 fluctuation can be reduced using a re-ordered segmented EPI ACS based on the fast low-angle excitation echo-planar technique (FLEET). However, respiration-induced B0 fluctuations (exceeding 100 Hz at C7) are greater, and fewer k-space lines per slice are required for cervical spinal cord fMRI at 7 T, necessitating a separate evaluation of ACS methods. METHODS We compared 24-line single-shot EPI with 48-line two-shot segmented EPI, two-shot FLEET, and gradient echo (GRE)-based ACS acquisition methods, performed under various physiological conditions, in terms of temporal signal-to-noise ratio and prevalence of artifacts in generalized autocalibrating partially parallel acquisition (GRAPPA)-accelerated EPI of the cervical spinal cord at 7 T. RESULTS Segmented EPI and FLEET ACS produce images with nearly identical patterns of severe image artifacts. GRE and single-shot EPI ACS consistently produce images free from significant artifacts, and temporal signal-to-noise ratio is significantly greater for GRE ACS, particularly in lower slices where through-slice dephasing is most severe. CONCLUSIONS GRE and single-shot EPI-ACS acquisition methods, which are robust to respiration-induced phase errors between k-space segments, produce images with fewer and less severe artifacts than either FLEET or conventionally segmented EPI for accelerated EPI of the cervical spinal cord at 7 T.
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Affiliation(s)
- Alan C. Seifert
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Junqian Xu
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY USA
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20
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Benson NC, Yoon JMD, Forenzo D, Engel SA, Kay KN, Winawer J. Variability of the Surface Area of the V1, V2, and V3 Maps in a Large Sample of Human Observers. J Neurosci 2022; 42:8629-8646. [PMID: 36180226 PMCID: PMC9671582 DOI: 10.1523/jneurosci.0690-21.2022] [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: 04/01/2021] [Revised: 09/08/2022] [Accepted: 09/16/2022] [Indexed: 11/21/2022] Open
Abstract
How variable is the functionally defined structure of early visual areas in human cortex and how much variability is shared between twins? Here we quantify individual differences in the best understood functionally defined regions of cortex: V1, V2, V3. The Human Connectome Project 7T Retinotopy Dataset includes retinotopic measurements from 181 subjects (109 female, 72 male), including many twins. We trained four "anatomists" to manually define V1-V3 using retinotopic features. These definitions were more accurate than automated anatomical templates and showed that surface areas for these maps varied more than threefold across individuals. This threefold variation was little changed when normalizing visual area size by the surface area of the entire cerebral cortex. In addition to varying in size, we find that visual areas vary in how they sample the visual field. Specifically, the cortical magnification function differed substantially among individuals, with the relative amount of cortex devoted to central vision varying by more than a factor of 2. To complement the variability analysis, we examined the similarity of visual area size and structure across twins. Whereas the twin sample sizes are too small to make precise heritability estimates (50 monozygotic pairs, 34 dizygotic pairs), they nonetheless reveal high correlations, consistent with strong effects of the combination of shared genes and environment on visual area size. Collectively, these results provide the most comprehensive account of individual variability in visual area structure to date, and provide a robust population benchmark against which new individuals and developmental and clinical populations can be compared.SIGNIFICANCE STATEMENT Areas V1, V2, and V3 are among the best studied functionally defined regions in human cortex. Using the largest retinotopy dataset to date, we characterized the variability of these regions across individuals and the similarity between twin pairs. We find that the size of visual areas varies dramatically (up to 3.5×) across healthy young adults, far more than the variability of the cerebral cortex size as a whole. Much of this variability appears to arise from inherited factors, as we find very high correlations in visual area size between monozygotic twin pairs, and lower but still substantial correlations between dizygotic twin pairs. These results provide the most comprehensive assessment of how functionally defined visual cortex varies across the population to date.
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Affiliation(s)
- Noah C Benson
- eScience Institute, University of Washington, Seattle, Washington 98195
| | - Jennifer M D Yoon
- Department of Psychology, New York University, New York, New York 10003
- Center for Neural Sciences, New York University, New York, New York 10003
| | - Dylan Forenzo
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Stephen A Engel
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Kendrick N Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Jonathan Winawer
- Department of Psychology, New York University, New York, New York 10003
- Center for Neural Sciences, New York University, New York, New York 10003
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21
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Zhu W, Ma X, Zhu XH, Ugurbil K, Chen W, Wu X. Denoise Functional Magnetic Resonance Imaging With Random Matrix Theory Based Principal Component Analysis. IEEE Trans Biomed Eng 2022; 69:3377-3388. [PMID: 35439125 PMCID: PMC9579216 DOI: 10.1109/tbme.2022.3168592] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
High-resolution functional MRI (fMRI) is largely hindered by random thermal noise. Random matrix theory (RMT)-based principal component analysis (PCA) is promising to reduce such noise in fMRI data. However, there is no consensus about the optimal strategy and practice in implementation. In this work, we propose a comprehensive RMT-based denoising method that consists of 1) rank and noise estimation based on a set of newly derived multiple criteria, and 2) optimal singular value shrinkage, with each module explained and implemented based on the RMT. By incorporating the variance stabilizing approach, the denoising method can deal with low signal-to-noise ratio (SNR) (such as <5) magnitude fMRI data with favorable performance compared to other state-of-the-art methods. Results from both simulation and in-vivo high-resolution fMRI data show that the proposed denoising method dramatically improves image restoration quality, promoting functional sensitivity at the same level of functional mapping blurring compared to existing denoising methods. Moreover, the denoising method can serve as a drop-in step in data preprocessing pipelines along with other procedures aimed at removal of structured physiological noises. We expect that the proposed denoising method will play an important role in leveraging high-quality, high-resolution task fMRI, which is desirable in many neuroscience and clinical applications.
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22
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Miyata T, Benson NC, Winawer J, Takemura H. Structural Covariance and Heritability of the Optic Tract and Primary Visual Cortex in Living Human Brains. J Neurosci 2022; 42:6761-6769. [PMID: 35853720 PMCID: PMC9436011 DOI: 10.1523/jneurosci.0043-22.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 05/31/2022] [Accepted: 07/11/2022] [Indexed: 11/21/2022] Open
Abstract
Individual differences among human brains exist at many scales, spanning gene expression, white matter tissue properties, and the size and shape of cortical areas. One notable example is an approximately 3-fold range in the size of human primary visual cortex (V1), a much larger range than is found in overall brain size. A previous study (Andrews et al., 1997) reported a correlation between optic tract (OT) cross-section area and V1 size in postmortem human brains, suggesting that there may be a common developmental mechanism for multiple components of the visual pathways. We evaluated the relationship between properties of the OT and V1 in a much larger sample of living human brains by analyzing the Human Connectome Project (HCP) 7 Tesla Retinotopy Dataset (including 107 females and 71 males). This dataset includes retinotopic maps measured with functional MRI (fMRI) and fiber tract data measured with diffusion MRI (dMRI). We found a negative correlation between OT fractional anisotropy (FA) and V1 surface area (r = -0.19). This correlation, although small, was consistent across multiple dMRI datasets differing in acquisition parameters. Further, we found that both V1 surface area and OT properties were correlated among twins, with higher correlations for monozygotic (MZ) than dizygotic (DZ) twins, indicating a high degree of heritability for both properties. Together, these results demonstrate covariation across individuals in properties of the retina (OT) and cortex (V1) and show that each is influenced by genetic factors.SIGNIFICANCE STATEMENT The size of human primary visual cortex (V1) has large interindividual differences. These differences do not scale with overall brain size. A previous postmortem study reported a correlation between the size of the human optic tract (OT) and V1. In this study, we evaluated the relationship between the OT and V1 in living humans by analyzing a neuroimaging dataset that included functional MRI (fMRI) and diffusion MRI (dMRI) data. We found a small, but robust correlation between OT tissue properties and V1 size, supporting the existence of structural covariance between the OT and V1 in living humans. The results suggest that characteristics of retinal ganglion cells (RGCs), reflected in OT measurements, are correlated with individual differences in human V1.
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Affiliation(s)
- Toshikazu Miyata
- Graduate School of Frontier Biosciences, Osaka University, Suita-shi 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Institute, National Institute of Information and Communications Technology (NICT), Suita-shi 565-0871, Japan
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki-shi 444-8585, Japan
| | - Noah C Benson
- eScience Institute, University of Washington, Seattle, 98195, Washington
| | - Jonathan Winawer
- Department of Psychology and Center for Neural Science, New York University, New York, NY 10003
| | - Hiromasa Takemura
- Graduate School of Frontier Biosciences, Osaka University, Suita-shi 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Institute, National Institute of Information and Communications Technology (NICT), Suita-shi 565-0871, Japan
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki-shi 444-8585, Japan
- Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama-cho 240-0193, Japan
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23
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Meyer-Baese L, Watters H, Keilholz S. Spatiotemporal patterns of spontaneous brain activity: a mini-review. NEUROPHOTONICS 2022; 9:032209. [PMID: 35434180 PMCID: PMC9005199 DOI: 10.1117/1.nph.9.3.032209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 03/04/2022] [Indexed: 06/14/2023]
Abstract
The brain exists in a state of constant activity in the absence of any external sensory input. The spatiotemporal patterns of this spontaneous brain activity have been studied using various recording and imaging techniques. This has enabled considerable progress to be made in elucidating the cellular and network mechanisms that are involved in the observed spatiotemporal dynamics. This mini-review outlines different spatiotemporal dynamic patterns that have been identified in four commonly used modalities: electrophysiological recordings, optical imaging, functional magnetic resonance imaging, and electroencephalography. Signal sources for each modality, possible sources of the observed dynamics, and future directions are also discussed.
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Affiliation(s)
- Lisa Meyer-Baese
- Emory University, Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | | | - Shella Keilholz
- Emory University, Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
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24
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Lin T, Pehlivanoglu D, Ziaei M, Liu P, Woods AJ, Feifel D, Fischer H, Ebner NC. Age-Related Differences in Amygdala Activation Associated With Face Trustworthiness but No Evidence of Oxytocin Modulation. Front Psychol 2022; 13:838642. [PMID: 35814062 PMCID: PMC9262048 DOI: 10.3389/fpsyg.2022.838642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 05/31/2022] [Indexed: 11/27/2022] Open
Abstract
The amygdala has been shown to be responsive to face trustworthiness. While older adults typically give higher face trustworthiness ratings than young adults, a direct link between amygdala response and age-related differences in face trustworthiness evaluation has not yet been confirmed. Additionally, there is a possible modulatory role of the neuropeptide oxytocin in face trustworthiness evaluation, but the results are mixed and effects unexplored in aging. To address these research gaps, young, and older adults were randomly assigned to oxytocin or placebo self-administration via a nasal spray before rating faces on trustworthiness while undergoing functional magnetic resonance imaging. There was no overall age-group difference in face trustworthiness ratings, but older compared to young participants gave higher trustworthiness ratings to ambivalently untrustworthy-looking faces. In both age groups, lower face trustworthiness ratings were associated with higher left amygdala activity. A comparable negative linear association was observed in right amygdala but only among young participants. Also, in the right amygdala, lower and higher, compared to moderate, face trustworthiness ratings were associated with greater right amygdala activity (i.e., positive quadratic (U-shaped) association) for both age groups. Neither the behavioral nor the brain effects were modulated by a single dose of intranasal oxytocin administration, however. These results suggest dampened response to faces with lower trustworthiness among older compared to young adults, supporting the notion of reduced sensitivity to cues of untrustworthiness in aging. The findings also extend evidence of an age-related positivity effect to the evaluation of face trustworthiness.
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Affiliation(s)
- Tian Lin
- Department of Psychology, University of Florida, Gainesville, FL, United States
| | - Didem Pehlivanoglu
- Department of Psychology, University of Florida, Gainesville, FL, United States
| | - Maryam Ziaei
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Peiwei Liu
- Department of Psychology, University of Florida, Gainesville, FL, United States
| | - Adam J. Woods
- Department of Clinical and Health Psychology, Center for Cognitive Aging and Memory, University of Florida, Gainesville, FL, United States
| | - David Feifel
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Håkan Fischer
- Department of Psychology, University of Florida, Gainesville, FL, United States
- Department of Psychology, Stockholm University, Stockholm, Sweden
- Stockholm University Brain Imaging Centre (SUBIC), Stockholm, Sweden
| | - Natalie C. Ebner
- Department of Psychology, University of Florida, Gainesville, FL, United States
- Department of Clinical and Health Psychology, Center for Cognitive Aging and Memory, University of Florida, Gainesville, FL, United States
- Florida Institute for Cybersecurity Research, University of Florida, Gainesville, FL, United States
- Department of Aging and Geriatric Research, Institute on Aging, University of Florida, Gainesville, FL, United States
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25
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Altered hippocampus and amygdala subregion connectome hierarchy in major depressive disorder. Transl Psychiatry 2022; 12:209. [PMID: 35589678 PMCID: PMC9120054 DOI: 10.1038/s41398-022-01976-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 05/04/2022] [Accepted: 05/10/2022] [Indexed: 01/04/2023] Open
Abstract
The hippocampus and amygdala limbic structures are critical to the etiology of major depressive disorder (MDD). However, there are no high-resolution characterizations of the role of their subregions in the whole brain network (connectome). Connectomic examination of these subregions can uncover disorder-related patterns that are otherwise missed when treated as single structures. 38 MDD patients and 40 healthy controls (HC) underwent anatomical and diffusion imaging using 7-Tesla MRI. Whole-brain segmentation was performed along with hippocampus and amygdala subregion segmentation, each representing a node in the connectome. Graph theory analysis was applied to examine the importance of the limbic subregions within the brain network using centrality features measured by node strength (sum of weights of the node's connections), Betweenness (number of shortest paths that traverse the node), and clustering coefficient (how connected the node's neighbors are to one another and forming a cluster). Compared to HC, MDD patients showed decreased node strength of the right hippocampus cornu ammonis (CA) 3/4, indicating decreased connectivity to the rest of the brain, and decreased clustering coefficient of the right dentate gyrus, implying it is less embedded in a cluster. Additionally, within the MDD group, the greater the embedding of the right amygdala central nucleus (CeA) in a cluster, the greater the severity of depressive symptoms. The altered role of these limbic subregions in the whole-brain connectome is related to diagnosis and depression severity, contributing to our understanding of the limbic system involvement in MDD and may elucidate the underlying mechanisms of depression.
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26
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Ma X, Uğurbil K, Wu X. Mitigating transmit‐B
1
artifacts by predicting parallel transmission images with deep learning: A feasibility study using high‐resolution whole‐brain diffusion at 7 Tesla. Magn Reson Med 2022; 88:727-741. [PMID: 35403237 PMCID: PMC9324974 DOI: 10.1002/mrm.29238] [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: 10/06/2021] [Revised: 02/24/2022] [Accepted: 02/28/2022] [Indexed: 11/12/2022]
Abstract
Purpose To propose a novel deep learning (DL) approach to transmit‐B1 (B1+)‐artifact mitigation without direct use of parallel transmission (pTx), by predicting pTx images from single‐channel transmission (sTx) images. Methods A deep encoder–decoder convolutional neural network was constructed and trained to learn the mapping from sTx to pTx images. The feasibility was demonstrated using 7 T Human‐Connectome Project (HCP)‐style diffusion MRI. The training dataset comprised images acquired on 5 healthy subjects using commercial Nova RF coils. Relevant hyperparameters were tuned with a nested cross‐validation, and the generalization performance evaluated using a regular cross‐validation. Results Our DL method effectively improved the image quality for sTx images by restoring the signal dropout, with quality measures (including normalized root‐mean‐square error, peak SNR, and structural similarity index measure) improved in most brain regions. The improved image quality was translated into improved performances for diffusion tensor imaging analysis; our method improved accuracy for fractional anisotropy and mean diffusivity estimations, reduced the angular errors of principal eigenvectors, and improved the fiber orientation delineation relative to sTx images. Moreover, the final DL model trained on data of all 5 subjects was successfully used to predict pTx images for unseen new subjects (randomly selected from the 7 T HCP database), effectively recovering the signal dropout and improving color‐coded fractional anisotropy maps with largely reduced noise levels. Conclusion The proposed DL method has potential to provide images with reduced B1+ artifacts in healthy subjects even when pTx resources are inaccessible on the user side.
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Affiliation(s)
- Xiaodong Ma
- Center for Magnetic Resonance Research, Radiology, Medical School University of Minnesota Minneapolis Minnesota USA
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, Radiology, Medical School University of Minnesota Minneapolis Minnesota USA
| | - Xiaoping Wu
- Center for Magnetic Resonance Research, Radiology, Medical School University of Minnesota Minneapolis Minnesota USA
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27
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Hu G, Li H, Zhao W, Hao Y, Bai Z, Nickerson LD, Cong F. Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data. Neuroimage 2022; 255:119193. [PMID: 35398543 DOI: 10.1016/j.neuroimage.2022.119193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 02/23/2022] [Accepted: 04/06/2022] [Indexed: 11/19/2022] Open
Abstract
The study of brain network interactions during naturalistic stimuli facilitates a deeper understanding of human brain function. To estimate large-scale brain networks evoked with naturalistic stimuli, a tensor component analysis (TCA) based framework was used to characterize shared spatio-temporal patterns across subjects in a purely data-driven manner. In this framework, a third-order tensor is constructed from the timeseries extracted from all brain regions from a given parcellation, for all participants, with modes of the tensor corresponding to spatial distribution, time series and participants. TCA then reveals spatially and temporally shared components, i.e., evoked networks with the naturalistic stimuli, their time courses of activity and subject loadings of each component. To enhance the reproducibility of the estimation with the adaptive TCA algorithm, a novel spectral clustering method, tensor spectral clustering, was proposed and applied to evaluate the stability of the TCA algorithm. We demonstrated the effectiveness of the proposed framework via simulations and real fMRI data collected during a motor task with a traditional fMRI study design. We also applied the proposed framework to fMRI data collected during passive movie watching to illustrate how reproducible brain networks are evoked by naturalistic movie viewing.
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Affiliation(s)
- Guoqiang Hu
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China.
| | - Huanjie Li
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Wei Zhao
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Yuxing Hao
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Zonglei Bai
- School of Electronics Engineering and Computer Science, Peking University, Beijing, China
| | - Lisa D Nickerson
- Brain Imaging Center, Mclean Hospital, Belmont, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Fengyu Cong
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China; School of Artificial Intelligence, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China; Key Laboratory of Integrated Circuit and Biomedical Electronic System, Liaoning Province. Dalian University of Technology, Dalian, China; Faculty of Information Technology, University of Jyvaskyla, Jyvaskyla, Finland.
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28
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Yun SD, Pais-Roldán P, Palomero-Gallagher N, Shah NJ. Mapping of whole-cerebrum resting-state networks using ultra-high resolution acquisition protocols. Hum Brain Mapp 2022; 43:3386-3403. [PMID: 35384130 PMCID: PMC9248311 DOI: 10.1002/hbm.25855] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/17/2022] [Accepted: 03/25/2022] [Indexed: 12/28/2022] Open
Abstract
Resting‐state functional magnetic resonance imaging (fMRI) has been used in numerous studies to map networks in the brain that employ spatially disparate regions. However, attempts to map networks with high spatial resolution have been hampered by conflicting technical demands and associated problems. Results from recent fMRI studies have shown that spatial resolution remains around 0.7 × 0.7 × 0.7 mm3, with only partial brain coverage. Therefore, this work aims to present a novel fMRI technique that was developed based on echo‐planar‐imaging with keyhole (EPIK) combined with repetition‐time‐external (TR‐external) EPI phase correction. Each technique has been previously shown to be effective in enhancing the spatial resolution of fMRI, and in this work, the combination of the two techniques into TR‐external EPIK provided a nominal spatial resolution of 0.51 × 0.51 × 1.00 mm3 (0.26 mm3 voxel) with whole‐cerebrum coverage. Here, the feasibility of using half‐millimetre in‐plane TR‐external EPIK for resting‐state fMRI was validated using 13 healthy subjects and the corresponding reproducible mapping of resting‐state networks was demonstrated. Furthermore, TR‐external EPIK enabled the identification of various resting‐state networks distributed throughout the brain from a single fMRI session, with mapping fidelity onto the grey matter at 7T. The high‐resolution functional image further revealed mesoscale anatomical structures, such as small cerebral vessels and the internal granular layer of the cortex within the postcentral gyrus.
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Affiliation(s)
- Seong Dae Yun
- Institute of Neuroscience and Medicine-4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Patricia Pais-Roldán
- Institute of Neuroscience and Medicine-4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine-1, Structural and Functional Organisation of the Brain, Forschungszentrum Jülich, Jülich, Germany.,C. & O. Vogt Institute for Brain Research, Heinrich-Heine-University, Düsseldorf, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine-4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany.,Institute of Neuroscience and Medicine-11, Molecular Neuroscience and Neuroimaging, JARA, Forschungszentrum Jülich, Jülich, Germany.,JARA - BRAIN - Translational Medicine, Aachen, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
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29
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Golesorkhi M, Gomez-Pilar J, Çatal Y, Tumati S, Yagoub MCE, Stamatakis EA, Northoff G. From temporal to spatial topography: hierarchy of neural dynamics in higher- and lower-order networks shapes their complexity. Cereb Cortex 2022; 32:5637-5653. [PMID: 35188968 PMCID: PMC9753094 DOI: 10.1093/cercor/bhac042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/25/2023] Open
Abstract
The brain shows a topographical hierarchy along the lines of lower- and higher-order networks. The exact temporal dynamics characterization of this lower-higher-order topography at rest and its impact on task states remains unclear, though. Using 2 functional magnetic resonance imaging data sets, we investigate lower- and higher-order networks in terms of the signal compressibility, operationalized by Lempel-Ziv complexity (LZC). As we assume that this degree of complexity is related to the slow-fast frequency balance, we also compute the median frequency (MF), an estimation of frequency distribution. We demonstrate (i) topographical differences at rest between higher- and lower-order networks, showing lower LZC and MF in the former; (ii) task-related and task-specific changes in LZC and MF in both lower- and higher-order networks; (iii) hierarchical relationship between LZC and MF, as MF at rest correlates with LZC rest-task change along the lines of lower- and higher-order networks; and (iv) causal and nonlinear relation between LZC at rest and LZC during task, with MF at rest acting as mediator. Together, results show that the topographical hierarchy of lower- and higher-order networks converges with their temporal hierarchy, with these neural dynamics at rest shaping their range of complexity during task states in a nonlinear way.
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Affiliation(s)
| | | | - Yasir Çatal
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa ON K1Z 7K4, Canada
| | - Shankar Tumati
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa ON K1Z 7K4, Canada
| | - Mustapha C E Yagoub
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa ON K1Z 7K4, Canada
| | - Emanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB1 0SP, United Kingdom
| | - Georg Northoff
- Corresponding author: Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada.
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30
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Medial temporal lobe contributions to resting-state networks. Brain Struct Funct 2022; 227:995-1012. [PMID: 35041057 PMCID: PMC8930967 DOI: 10.1007/s00429-021-02442-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/13/2021] [Indexed: 12/31/2022]
Abstract
The medial temporal lobe (MTL) is a set of interconnected brain regions that have been shown to play a central role in behavior as well as in neurological disease. Recent studies using resting-state functional magnetic resonance imaging (rsfMRI) have attempted to understand the MTL in terms of its functional connectivity with the rest of the brain. However, the exact characterization of the whole-brain networks that co-activate with the MTL as well as how the various sub-regions of the MTL are associated with these networks remains poorly understood. Here, we attempted to advance these issues by exploiting the high spatial resolution 7T rsfMRI dataset from the Human Connectome Project with a data-driven analysis approach that relied on independent component analysis (ICA) restricted to the MTL. We found that four different well-known resting-state networks co-activated with a unique configuration of MTL subcomponents. Specifically, we found that different sections of the parahippocampal cortex were involved in the default mode, visual and dorsal attention networks; sections of the hippocampus in the somatomotor and default mode networks; and the lateral entorhinal cortex in the dorsal attention network. We replicated this set of results in a validation sample. These results provide new insight into how the MTL and its subcomponents contribute to known resting-state networks. The participation of the MTL in an expanded range of resting-state networks is in line with recent proposals on MTL function.
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31
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Lavigne KM, Kanagasabai K, Palaniyappan L. Ultra-high field neuroimaging in psychosis: A narrative review. Front Psychiatry 2022; 13:994372. [PMID: 36506432 PMCID: PMC9730890 DOI: 10.3389/fpsyt.2022.994372] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/08/2022] [Indexed: 11/27/2022] Open
Abstract
Schizophrenia and related psychoses are complex neuropsychiatric diseases representing dysconnectivity across multiple scales, through the micro (cellular), meso (brain network), manifest (behavioral), and social (interpersonal) levels. In vivo human neuroimaging, particularly at ultra-high field (UHF), offers unprecedented opportunity to examine multiscale dysconnectivity in psychosis. In this review, we provide an overview of the literature to date on UHF in psychosis, focusing on microscale findings from magnetic resonance spectroscopy (MRS), mesoscale studies on structural and functional magnetic resonance imaging (fMRI), and multiscale studies assessing multiple neuroimaging modalities and relating UHF findings to behavior. We highlight key insights and considerations from multiscale and longitudinal studies and provide recommendations for future research on UHF neuroimaging in psychosis.
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Affiliation(s)
- Katie M Lavigne
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute-Hospital, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Kesavi Kanagasabai
- Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada.,Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
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32
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Yang L, Wei J, Li Y, Wang B, Guo H, Yang Y, Xiang J. Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI. Brain Sci 2021; 12:brainsci12010066. [PMID: 35053813 PMCID: PMC8773904 DOI: 10.3390/brainsci12010066] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/23/2021] [Accepted: 12/28/2021] [Indexed: 11/16/2022] Open
Abstract
In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.
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Affiliation(s)
| | | | | | | | | | | | - Jie Xiang
- Correspondence: ; Tel.: +86-186-0351-1178
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33
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Kline A, Forkert ND, Felfeliyan B, Pittman D, Goodyear B, Ronsky J. fMRI-Informed EEG for brain mapping of imagined lower limb movement: Feasibility of a brain computer interface. J Neurosci Methods 2021; 363:109339. [PMID: 34454954 DOI: 10.1016/j.jneumeth.2021.109339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 08/17/2021] [Accepted: 08/21/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND EEG and fMRI have contributed greatly to our understanding of brain activity and its link to behaviors by helping to identify both when and where the activity occurs. This is particularly important in the development of brain-computer interfaces (BCIs), where feed forward systems gather data from imagined brain activity and then send that information to an effector. The purpose of this study was to develop and evaluate a computational approach that enables an accurate mapping of spatial brain activity (fMRI) in relation to the temporal receptors (EEG electrodes) associated with imagined lower limb movement. NEW METHOD EEG and fMRI data from 16 healthy, male participants while imagining lower limb movement were used for this purpose. A combined analysis of fMRI data and EEG electrode locations was developed to identify EEG electrodes with a high likelihood of capturing imagined lower limb movement originating from various clusters of brain activity. This novel feature selection tool was used to develop an artificial neural network model to classify right and left lower limb movement. RESULTS Results showed that left versus right lower limb imagined movement could be classified with 66.5% accuracy using this approach. Comparison with existing methods: Adopting a purely data-driven approach for feature selection to use in the right/left classification task resulted in the same accuracy (66.6%) but with reduced interpretability. CONCLUSIONS The developed fMRI-informed EEG approach could pave the way towards improved brain computer interfaces for lower limb movement while also being applicable to other systems where fMRI could be helpful to inform EEG acquisition and processing.
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Affiliation(s)
- Adrienne Kline
- Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada.
| | - Nils D Forkert
- Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada
| | - Banafshe Felfeliyan
- Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada
| | - Daniel Pittman
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
| | - Bradley Goodyear
- Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, University of Calgary, Calgary, Alberta, Canada
| | - Janet Ronsky
- Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada
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Cognitive control affects motor learning through local variations in GABA within the primary motor cortex. Sci Rep 2021; 11:18566. [PMID: 34535725 PMCID: PMC8448760 DOI: 10.1038/s41598-021-97974-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 08/27/2021] [Indexed: 02/08/2023] Open
Abstract
The primary motor cortex (M1) is crucial for motor learning; however, its interaction with other brain areas during motor learning remains unclear. We hypothesized that the fronto-parietal execution network (FPN) provides learning-related information critical for the flexible cognitive control that is required for practice. We assessed network-level changes during sequential finger tapping learning under speed pressure by combining magnetic resonance spectroscopy and task and resting-state functional magnetic resonance imaging. There was a motor learning-related increase in preparatory activity in the fronto-parietal regions, including the right M1, overlapping the FPN and sensorimotor network (SMN). Learning-related increases in M1-seeded functional connectivity with the FPN, but not the SMN, were associated with decreased GABA/glutamate ratio in the M1, which were more prominent in the parietal than the frontal region. A decrease in the GABA/glutamate ratio in the right M1 was positively correlated with improvements in task performance (p = 0.042). Our findings indicate that motor learning driven by cognitive control is associated with local variations in the GABA/glutamate ratio in the M1 that reflects remote connectivity with the FPN, representing network-level motor sequence learning formations.
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Abstract
Food and Drug Administration approval of 7T MR imaging allows ultrahigh-field neuroimaging to extend from the research realm into the clinical realm. Increased signal is clinically advantageous for smaller voxels and thereby high spatial resolution imaging, with additional advantages of increased tissue contrast. Susceptibility, time-of-flight signal, and blood oxygen level-dependent signal also have favorable clinical benefit from 7T. This article provides a survey of clinical cases showcasing some advantages of 7T.
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36
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Dowdle LT, Ghose G, Chen CCC, Ugurbil K, Yacoub E, Vizioli L. Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI. Prog Neurobiol 2021; 207:102171. [PMID: 34492308 DOI: 10.1016/j.pneurobio.2021.102171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 08/09/2021] [Accepted: 09/02/2021] [Indexed: 01/25/2023]
Abstract
Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States
| | - Clark C C Chen
- Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States.
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Misra J, Surampudi SG, Venkatesh M, Limbachia C, Jaja J, Pessoa L. Learning brain dynamics for decoding and predicting individual differences. PLoS Comput Biol 2021; 17:e1008943. [PMID: 34478442 PMCID: PMC8445454 DOI: 10.1371/journal.pcbi.1008943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 09/16/2021] [Accepted: 08/19/2021] [Indexed: 12/04/2022] Open
Abstract
Insights from functional Magnetic Resonance Imaging (fMRI), as well as recordings of large numbers of neurons, reveal that many cognitive, emotional, and motor functions depend on the multivariate interactions of brain signals. To decode brain dynamics, we propose an architecture based on recurrent neural networks to uncover distributed spatiotemporal signatures. We demonstrate the potential of the approach using human fMRI data during movie-watching data and a continuous experimental paradigm. The model was able to learn spatiotemporal patterns that supported 15-way movie-clip classification (∼90%) at the level of brain regions, and binary classification of experimental conditions (∼60%) at the level of voxels. The model was also able to learn individual differences in measures of fluid intelligence and verbal IQ at levels comparable to that of existing techniques. We propose a dimensionality reduction approach that uncovers low-dimensional trajectories and captures essential informational (i.e., classification related) properties of brain dynamics. Finally, saliency maps and lesion analysis were employed to characterize brain-region/voxel importance, and uncovered how dynamic but consistent changes in fMRI activation influenced decoding performance. When applied at the level of voxels, our framework implements a dynamic version of multivariate pattern analysis. Our approach provides a framework for visualizing, analyzing, and discovering dynamic spatially distributed brain representations during naturalistic conditions.
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Affiliation(s)
- Joyneel Misra
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America
| | - Srinivas Govinda Surampudi
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America
| | - Manasij Venkatesh
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America
| | - Chirag Limbachia
- Department of Psychology and Maryland Neuroimaging Center, University of Maryland, College Park, Maryland, United States of America
| | - Joseph Jaja
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America
| | - Luiz Pessoa
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America
- Department of Psychology and Maryland Neuroimaging Center, University of Maryland, College Park, Maryland, United States of America
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38
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Autio JA, Zhu Q, Li X, Glasser MF, Schwiedrzik CM, Fair DA, Zimmermann J, Yacoub E, Menon RS, Van Essen DC, Hayashi T, Russ B, Vanduffel W. Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection. Neuroimage 2021; 236:118082. [PMID: 33882349 PMCID: PMC8594288 DOI: 10.1016/j.neuroimage.2021.118082] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/16/2021] [Accepted: 04/07/2021] [Indexed: 02/07/2023] Open
Abstract
Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.
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Affiliation(s)
- Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Qi Zhu
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium; Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France
| | - Xiaolian Li
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium
| | - Matthew F Glasser
- Departments of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Departments of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Caspar M Schwiedrzik
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077 Göttingen, Germany; Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Damien A Fair
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jan Zimmermann
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
| | - David C Van Essen
- Departments of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Brian Russ
- Department of Psychiatry, New York University Langone, New York City, New York, USA; Center for the Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, New York, USA; Department of Neuroscience, Icahn School of Medicine, Mount Sinai, New York City, New York, USA
| | - Wim Vanduffel
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium; Leuven Brain Institute, KU Leuven, Leuven 3000, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
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39
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Reducing SAR in 7T brain fMRI by circumventing fat suppression while removing the lipid signal through a parallel acquisition approach. Sci Rep 2021; 11:15371. [PMID: 34321529 PMCID: PMC8319205 DOI: 10.1038/s41598-021-94692-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 07/09/2021] [Indexed: 12/14/2022] Open
Abstract
Ultra-high-field functional magnetic resonance imaging (fMRI) offers a way to new insights while increasing the spatial and temporal resolution. However, a crucial concern in 7T human MRI is the increase in power deposition, supervised through the specific absorption rate (SAR). The SAR limitation can restrict the brain coverage or the minimal repetition time of fMRI experiments. In the majority of today’s studies fMRI relies on the well-known gradient-echo echo-planar imaging (GRE-EPI) sequence, which offers ultrafast acquisition. Commonly, the GRE-EPI sequence comprises two pulses: fat suppression and excitation. This work provides the means for a significant reduction in the SAR by circumventing the fat-suppression pulse. Without this fat-suppression, however, lipid signal can result in artifacts due to the chemical shift between the lipid and water signals. Our approach exploits a reconstruction similar to the simultaneous-multi-slice method to separate the lipid and water images, thus avoiding undesired lipid artifacts in brain images. The lipid-water separation is based on the known spatial shift of the lipid signal, which can be detected by the multi-channel coils sensitivity profiles. Our study shows robust human imaging, offering greater flexibility to reduce the SAR, shorten the repetition time or increase the volume coverage with substantial benefit for brain functional studies.
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40
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Structural and resting state functional connectivity beyond the cortex. Neuroimage 2021; 240:118379. [PMID: 34252527 DOI: 10.1016/j.neuroimage.2021.118379] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/21/2021] [Accepted: 07/07/2021] [Indexed: 12/14/2022] Open
Abstract
Mapping the structural and functional connectivity of the central nervous system has become a key area within neuroimaging research. While detailed network structures across the entire brain have been probed using animal models, non-invasive neuroimaging in humans has thus far been dominated by cortical investigations. Beyond the cortex, subcortical nuclei have traditionally been less accessible due to their smaller size and greater distance from radio frequency coils. However, major neuroimaging developments now provide improved signal and the resolution required to study these structures. Here, we present an overview of the connectivity between the amygdala, brainstem, cerebellum, spinal cord and the rest of the brain. While limitations to their imaging and analyses remain, we also provide some recommendations and considerations for mapping brain connectivity beyond the cortex.
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41
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Schallmo MP, Weldon KB, Burton PC, Sponheim SR, Olman CA. Assessing methods for geometric distortion compensation in 7 T gradient echo functional MRI data. Hum Brain Mapp 2021; 42:4205-4223. [PMID: 34156132 PMCID: PMC8356998 DOI: 10.1002/hbm.25540] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 04/22/2021] [Accepted: 04/26/2021] [Indexed: 11/13/2022] Open
Abstract
Echo planar imaging (EPI) is widely used in functional and diffusion‐weighted MRI, but suffers from significant geometric distortions in the phase encoding direction caused by inhomogeneities in the static magnetic field (B0). This is a particular challenge for EPI at very high field (≥7 T), as distortion increases with higher field strength. A number of techniques for distortion correction exist, including those based on B0 field mapping and acquiring EPI scans with opposite phase encoding directions. However, few quantitative comparisons of distortion compensation methods have been performed using human EPI data, especially at very high field. Here, we compared distortion compensation using B0 field maps and opposite phase encoding scans in two different software packages (FSL and AFNI) applied to 7 T gradient echo (GE) EPI data from 31 human participants. We assessed distortion compensation quality by quantifying alignment to anatomical reference scans using Dice coefficients and mutual information. Performance between FSL and AFNI was equivalent. In our whole‐brain analyses, we found superior distortion compensation using GE scans with opposite phase encoding directions, versus B0 field maps or spin echo (SE) opposite phase encoding scans. However, SE performed better when analyses were limited to ventromedial prefrontal cortex, a region with substantial dropout. Matching the type of opposite phase encoding scans to the EPI data being corrected (e.g., SE‐to‐SE) also yielded better distortion correction. While the ideal distortion compensation approach likely varies depending on methodological differences across experiments, this study provides a framework for quantitative comparison of different distortion compensation methods.
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Affiliation(s)
- Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA
| | - Kimberly B Weldon
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Philip C Burton
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Office of the College of Liberal Arts Associate Dean for Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Scott R Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA.,Veterans Affairs Medical Center, Minneapolis, Minnesota, USA
| | - Cheryl A Olman
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
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42
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Abstract
Functional magnetic resonance imaging (fMRI) has become one of the most powerful tools for investigating the human brain. Ultrahigh magnetic field (UHF) of 7 Tesla has played a critical role in enabling higher resolution and more accurate (relative to the neuronal activity) functional maps. However, even with these gains, the fMRI approach is challenged relative to the spatial scale over which brain function is organized. Therefore, going forward, significant advances in fMRI are still needed. Such advances will predominantly come from magnetic fields significantly higher than 7 Tesla, which is the most commonly used UHF platform today, and additional technologies that will include developments in pulse sequences, image reconstruction, noise suppression, and image analysis in order to further enhance and augment the gains than can be realized by going to higher magnetic fields.
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Affiliation(s)
- Kamil Uğurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 6 Street SE, Minneapolis, MN 55456
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43
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Khosla M, Ngo GH, Jamison K, Kuceyeski A, Sabuncu MR. Cortical response to naturalistic stimuli is largely predictable with deep neural networks. SCIENCE ADVANCES 2021; 7:7/22/eabe7547. [PMID: 34049888 PMCID: PMC8163078 DOI: 10.1126/sciadv.abe7547] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 04/12/2021] [Indexed: 05/08/2023]
Abstract
Naturalistic stimuli, such as movies, activate a substantial portion of the human brain, invoking a response shared across individuals. Encoding models that predict neural responses to arbitrary stimuli can be very useful for studying brain function. However, existing models focus on limited aspects of naturalistic stimuli, ignoring the dynamic interactions of modalities in this inherently context-rich paradigm. Using movie-watching data from the Human Connectome Project, we build group-level models of neural activity that incorporate several inductive biases about neural information processing, including hierarchical processing, temporal assimilation, and auditory-visual interactions. We demonstrate how incorporating these biases leads to remarkable prediction performance across large areas of the cortex, beyond the sensory-specific cortices into multisensory sites and frontal cortex. Furthermore, we illustrate that encoding models learn high-level concepts that generalize to task-bound paradigms. Together, our findings underscore the potential of encoding models as powerful tools for studying brain function in ecologically valid conditions.
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Affiliation(s)
- Meenakshi Khosla
- School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
| | - Gia H Ngo
- School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
| | - Keith Jamison
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Mert R Sabuncu
- School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Nancy E. & Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
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44
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Sahasrabudhe SA, Silamongkol T, Park YW, Colette A, Eberly LE, Klimes-Dougan B, Coles LD, Cloyd JC, Öz G, Mueller BA, Kartha RV, Cullen KR. Identifying Biological Signatures of N-Acetylcysteine for Non-Suicidal Self-Injury in Adolescents and Young Adults. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2021; 6:e210007. [PMID: 34036177 PMCID: PMC8143039 DOI: 10.20900/jpbs.20210007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The prevalence of non-suicidal self-injury (NSSI) is high in adolescents and young adults. However, there is a paucity of evidence-based treatments to address this clinical problem. An open-label, pilot study in the target population showed that treatment with oral N-acetylcysteine (NAC), a widely available dietary supplement, was associated with reduction in NSSI frequency. In preparation for a biologically informed design of an efficacy trial, a critical preliminary step is to clarify NAC's biological signatures, or measures of the mechanisms underlying its clinical effects. Toward that end, we propose a 2-stage project to investigate NAC's biological signatures (changes in glutathione (GSH) and/or glutamate (Glu)) in women with NSSI. The first stage; a double-blind randomized placebo-controlled study will focus on identifying the optimal dose to achieve meaningful change in GSH and Glu during short-term (4 weeks) NAC treatment in 36 women aged 16-24 years with NSSI. Go/No-go criteria to determine if the study will progress to the second stage include pre-specified changes in brain and blood measures of GSH. Changes in the brain GSH are measured through magnetic resonance spectroscopy (MRS). The dose for the stage 2 will be selected based on the biological changes and the tolerability observed in the stage 1. The stage 2 will seek to replicate the biological signature findings in an 8-week trial in a new patient cohort, and examine the relationships among biological signatures, NAC pharmacokinetics and clinical response. This 2-stage project is unique as it unifies clinical psychiatric measurements, quantitative MRS and pharmacological approaches in the first placebo-controlled clinical trial of NAC in young women with NSSI. TRIAL REGISTRATION The stage 1 trial protocol has been registered on https://clinicaltrials.gov/ with ClinicalTrials.gov ID "NCT04005053" (Registered on 02 July 2019. Available from: https://clinicaltrials.gov/ct2/show/NCT04005053).
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Affiliation(s)
- Siddhee A. Sahasrabudhe
- Center for Orphan Drug Research, Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN 55455, USA
| | - Thanharat Silamongkol
- Department of Psychiatry and Behavioral Sciences, Medical School, University of Minnesota, Minneapolis, MN 55454, USA
| | - Young Woo Park
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Alanna Colette
- Department of Psychiatry and Behavioral Sciences, Medical School, University of Minnesota, Minneapolis, MN 55454, USA
| | - Lynn E. Eberly
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
- School of Public Health, Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Bonnie Klimes-Dougan
- Department of Psychology, College of Liberal Arts, University of Minnesota, Minneapolis, MN 55455, USA
| | - Lisa D. Coles
- Center for Orphan Drug Research, Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN 55455, USA
| | - James C. Cloyd
- Center for Orphan Drug Research, Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN 55455, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Bryon A. Mueller
- Department of Psychiatry and Behavioral Sciences, Medical School, University of Minnesota, Minneapolis, MN 55454, USA
| | - Reena V. Kartha
- Center for Orphan Drug Research, Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN 55455, USA
| | - Kathryn R. Cullen
- Department of Psychiatry and Behavioral Sciences, Medical School, University of Minnesota, Minneapolis, MN 55454, USA
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45
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Dowdle LT, Ghose G, Ugurbil K, Yacoub E, Vizioli L. Clarifying the role of higher-level cortices in resolving perceptual ambiguity using ultra high field fMRI. Neuroimage 2021; 227:117654. [PMID: 33333319 PMCID: PMC10614695 DOI: 10.1016/j.neuroimage.2020.117654] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/17/2020] [Accepted: 12/05/2020] [Indexed: 12/17/2022] Open
Abstract
The brain is organized into distinct, flexible networks. Within these networks, cognitive variables such as attention can modulate sensory representations in accordance with moment-to-moment behavioral requirements. These modulations can be studied by varying task demands; however, the tasks employed are often incongruent with the postulated functions of a sensory system, limiting the characterization of the system in relation to natural behaviors. Here we combine domain-specific task manipulations and ultra-high field fMRI to study the nature of top-down modulations. We exploited faces, a visual category underpinned by a complex cortical network, and instructed participants to perform either a stimulus-relevant/domain-specific or a stimulus-irrelevant task in the scanner. We found that 1. perceptual ambiguity (i.e. difficulty of achieving a stable percept) is encoded in top-down modulations from higher-level cortices; 2. the right inferior-temporal lobe is active under challenging conditions and uniquely encodes trial-by-trial variability in face perception.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN 55455.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN 55455
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN 55455.
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46
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Yacoub E, Grier MD, Auerbach EJ, Lagore RL, Harel N, Adriany G, Zilverstand A, Hayden BY, Heilbronner SR, Uğurbil K, Zimmermann J. Ultra-high field (10.5 T) resting state fMRI in the macaque. Neuroimage 2020; 223:117349. [PMID: 32898683 PMCID: PMC7745777 DOI: 10.1016/j.neuroimage.2020.117349] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/20/2020] [Accepted: 08/31/2020] [Indexed: 01/02/2023] Open
Abstract
Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for contrast agents limiting translatability, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, imaging at magnetic fields above 7T has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed single-subject resting state analysis at high resolutions using a 10.5 Tesla scanner. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI 'macaque connectome' will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics.
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Affiliation(s)
- Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Mark D Grier
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States
| | - Edward J Auerbach
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Russell L Lagore
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, United States
| | - Gregor Adriany
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Anna Zilverstand
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55455, United States
| | - Benjamin Y Hayden
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Kamil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States.
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Zou X. Editorial for "Quantitative Evaluations of Geometrical Distortion Corrections in Cortical Surface-Based Analysis of High-Resolution Functional MRI Data at 7T". J Magn Reson Imaging 2020; 53:1235-1236. [PMID: 33210763 DOI: 10.1002/jmri.27447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 11/04/2020] [Indexed: 11/09/2022] Open
Affiliation(s)
- Xiaowei Zou
- MR Research & Collaboration, Siemens Medical Solutions USA Inc, Malvern, Pennsylvania, USA
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Mark IT, Black DF, DeLone DR, Passe TJ, Witte RJ, Little JT, Ho ML, Fagan AJ, Parney IF, Burns TC, Welker KM. Higher temporal resolution multiband fMRI provides improved presurgical language maps. Neuroradiology 2020; 63:439-445. [PMID: 33025042 DOI: 10.1007/s00234-020-02569-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 09/23/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE We investigated the hypothesis that increasing fMRI temporal resolution using a multiband (MB) gradient echo-echo planar imaging (GRE-EPI) pulse sequence provides fMRI language maps of higher statistical quality than those acquired with a traditional GRE-EPI sequence. METHODS This prospective study enrolled 29 consecutive patients receiving language fMRI prior to a potential brain resection for tumor, AVM, or epilepsy. A 4-min rhyming task was performed at 3.0 Tesla with a traditional GRE-EPI pulse sequence (TR = 2000, TE = 30, matrix = 64/100%, slice = 4/0, FOV = 24, slices = 30, time points = 120) and an additional MB GRE-EPI pulse sequence with an acceleration factor of 6 (TR = 333, TE = 30, matrix 64/100%, slice = 4/0, FOV = 24, time points = 720). Spatially filtered t statistical maps were generated. Volumes of interest (VOIs) were drawn around activations at Broca's, dorsolateral prefrontal cortex, Wernicke's, and the visual word form areas. The t value maxima were measured for the overall brain and each of the VOIs. A paired t test was performed for the corresponding traditional and MB GRE-EPI measurements. RESULTS The mean age of subjects was 42.6 years old (18-75). Sixty-two percent were male. The average overall brain t statistic maxima for the MB pulse sequence (t = 15.4) was higher than for the traditional pulse sequence (t = 9.3, p = < .0001). This also held true for Broca's area (p < 0.0001), Wernicke's area (p < .0001), dorsolateral prefrontal cortex (p < .0001), and the visual word form area (p < .0001). CONCLUSION A MB GRE-EPI fMRI pulse sequence employing high temporal resolution provides clinical fMRI language maps of greater statistical significance than those obtained with a traditional GRE-EPI sequence.
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Affiliation(s)
- Ian T Mark
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - David F Black
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - David R DeLone
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - Theodore J Passe
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - Robert J Witte
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - Jason T Little
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - Mai-Lan Ho
- Department of Radiology, Nationwide Children's Hospital, Columbus, OH, USA
| | - Andrew J Fagan
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA
| | - Ian F Parney
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, USA
| | | | - Kirk M Welker
- Department of Radiology, Mayo Clinic, 200 1st St. SW, Rochester, MN, 55905, USA.
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49
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Tian Y, Margulies DS, Breakspear M, Zalesky A. Topographic organization of the human subcortex unveiled with functional connectivity gradients. Nat Neurosci 2020; 23:1421-1432. [PMID: 32989295 DOI: 10.1038/s41593-020-00711-6] [Citation(s) in RCA: 226] [Impact Index Per Article: 56.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 08/21/2020] [Indexed: 12/14/2022]
Abstract
Brain atlases are fundamental to understanding the topographic organization of the human brain, yet many contemporary human atlases cover only the cerebral cortex, leaving the subcortex a terra incognita. We use functional MRI (fMRI) to map the complex topographic organization of the human subcortex, revealing large-scale connectivity gradients and new areal boundaries. We unveil four scales of subcortical organization that recapitulate well-known anatomical nuclei at the coarsest scale and delineate 27 new bilateral regions at the finest. Ultrahigh field strength fMRI corroborates and extends this organizational structure, enabling the delineation of finer subdivisions of the hippocampus and the amygdala, while task-evoked fMRI reveals a subtle subcortical reorganization in response to changing cognitive demands. A new subcortical atlas is delineated, personalized to represent individual differences and used to uncover reproducible brain-behavior relationships. Linking cortical networks to subcortical regions recapitulates a task-positive to task-negative axis. This new atlas enables holistic connectome mapping and characterization of cortico-subcortical connectivity.
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Affiliation(s)
- Ye Tian
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) UMR 8002, Integrative Neuroscience and Cognition Center, Université de Paris, Paris, France
| | - Michael Breakspear
- Discipline of Psychiatry, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia.,School of Psychology, Faculty of Science, University of Newcastle, Newcastle, New South Wales, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia. .,Department of Biomedical Engineering, Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia.
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50
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Min BK, Hämäläinen MS, Pantazis D. New Cognitive Neurotechnology Facilitates Studies of Cortical-Subcortical Interactions. Trends Biotechnol 2020; 38:952-962. [PMID: 32278504 PMCID: PMC7442676 DOI: 10.1016/j.tibtech.2020.03.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 03/06/2020] [Accepted: 03/06/2020] [Indexed: 11/26/2022]
Abstract
Most of the studies employing neuroimaging have focused on cortical and subcortical signals individually to obtain neurophysiological signatures of cognitive functions. However, understanding the dynamic communication between the cortex and subcortical structures is essential for unraveling the neural correlates of cognition. In this quest, magnetoencephalography (MEG) and electroencephalography (EEG) are the methods of choice because they are noninvasive electrophysiological recording techniques with high temporal resolution. Sophisticated MEG/EEG source estimation techniques and network analysis methods, developed recently, can provide a more comprehensive understanding of the neurophysiological mechanisms of fundamental cognitive processes. Used together with noninvasive modulation of cortical-subcortical communication, these approaches may open up new possibilities for expanding the repertoire of noninvasive cognitive neurotechnology.
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Affiliation(s)
- Byoung-Kyong Min
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Korea; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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