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Luppi AI, Golkowski D, Ranft A, Ilg R, Jordan D, Bzdok D, Owen AM, Naci L, Stamatakis EA, Amico E, Misic B. General anaesthesia decreases the uniqueness of brain functional connectivity across individuals and species. Nat Hum Behav 2025; 9:987-1004. [PMID: 40128306 PMCID: PMC12106074 DOI: 10.1038/s41562-025-02121-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 01/16/2025] [Indexed: 03/26/2025]
Abstract
The human brain is characterized by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI scans acquired under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain, both with respect to the brains of other individuals and the brains of another species. Using functional connectivity, we report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organized: it co-localizes with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol and reversed upon recovery. Providing convergent evidence, we show that anaesthesia shifts the functional connectivity of the human brain closer to the functional connectivity of the macaque brain in a low-dimensional space. Finally, anaesthesia diminishes the match between spontaneous brain activity and cognitive brain patterns aggregated from the Neurosynth meta-analytic engine. Collectively, the present results reveal that anaesthetized human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.
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Affiliation(s)
- Andrea I Luppi
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada.
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Daniel Golkowski
- Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Rudiger Ilg
- Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- Asklepios Clinic, Department of Neurology, Bad Tölz, Germany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
- Mila, Quebec Artificial Intelligence Institute, Montréal, Québec, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience, Western University, London, Ontario, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Emmanuel A Stamatakis
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Enrico Amico
- School of Mathematics, University of Birmingham, Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, UK
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
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2
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Zheng Y, Yang Y, Zhen Y, Wang X, Liu L, Zheng H, Tang S. Understanding Altered Dynamics in Cocaine Use Disorder Through State Transitions Mediated by Artificial Perturbations. Brain Sci 2025; 15:263. [PMID: 40149783 PMCID: PMC11939957 DOI: 10.3390/brainsci15030263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2025] [Revised: 02/26/2025] [Accepted: 02/26/2025] [Indexed: 03/29/2025] Open
Abstract
Background/Objectives: Cocaine use disorder (CUD) poses a worldwide health challenge, with severe consequences for brain function. However, the phase dynamics underlying CUD and the transitions between CUD and health remain poorly understood. Methods: Here, we used resting-state functional magnetic resonance imaging (fMRI) data from 43 CUD patients and 45 healthy controls (HCT). We performed empirical analysis to identify phase-coherence states and compared their probabilities of occurrence between conditions. To further explore the underlying mechanism, we employed computational modeling to replicate the observed state probabilities for each condition. These generated whole-brain models enabled us to simulate external perturbations and identify optimal brain regions mediating transitions between HCT and CUD. Results: We found that CUD was associated with a reduced occurrence probability of the state dominated by the default mode network (DMN). Perturbing the nucleus accumbens, thalamus, and specific regions within the default mode, limbic and frontoparietal networks drives transitions from HCT to CUD, while perturbing the hippocampus and specific regions within the visual, dorsal attention, and DMN facilitates a return from CUD to HCT. Conclusions: This study revealed altered DMN-related dynamics in CUD from the phase perspective and provides potential regions critical for state transitions. The results contribute to understanding the pathogenesis of CUD and the development of therapeutic stimulation strategies.
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Affiliation(s)
- Yi Zheng
- School of Mathematical Sciences, Beihang University, Beijing 100191, China
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
| | - Yaqian Yang
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
| | - Yi Zhen
- School of Mathematical Sciences, Beihang University, Beijing 100191, China
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
| | - Xin Wang
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- State Key Laboratory of Complex & Critical Software Environment, Beihang University, Beijing 100191, China
| | - Longzhao Liu
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- State Key Laboratory of Complex & Critical Software Environment, Beihang University, Beijing 100191, China
| | - Hongwei Zheng
- Beijing Academy of Blockchain and Edge Computing, Beijing 100085, China
| | - Shaoting Tang
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- State Key Laboratory of Complex & Critical Software Environment, Beihang University, Beijing 100191, China
- Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China
- Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China
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Pajavand AM, Grothe MJ, De Schotten MT, Giorgi FS, Vergallo A, Hampel H. Structural white matter connectivity differences independent of gray matter loss in mild cognitive impairment with neuropsychiatric symptoms: Early indicators of Alzheimer's disease using network-based statistics. J Alzheimers Dis 2024; 102:1042-1056. [PMID: 39574327 DOI: 10.1177/13872877241288710] [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] [Indexed: 12/28/2024]
Abstract
BACKGROUND Depression and circadian rhythm disruptions are non-cognitive neuropsychiatric symptoms (NPS) that can appear at any stage of the Alzheimer's disease (AD) continuum. Evidence suggests that NPS are linked to AD pathophysiology and hippocampal dysfunction. OBJECTIVE To examine structural white matter (WM) connectivity and its association with gray matter (GM) atrophy and to identify specific AD-related neural networks linked to NPS in individuals with mild cognitive impairment (MCI). METHODS Ninety-six older adults participants were divided into three groups based on the Global Depression Scale, Neuropsychiatric Inventory, Clinical Dementia Rating, and Mini-Mental Status Examination. Twelve individuals with MCI and NPS (MCI+) and 49 without NPS (MCI-) were classified, along with 35 age and gender-matched healthy individuals. Voxel-based morphometry and tract-based spatial statistics were employed to identify structural and microstructural alterations. Network-based statistics analyzed structural WM connectivity differences between MCI groups and healthy controls. RESULTS Significant structural WM connectivity and GM loss were exclusively observed in MCI+ individuals compared to controls. The hippocampus, amygdala, and sensory cortex showed GM atrophy (p < 0.05), while the thalamus, pallidum, putamen, caudate, hippocampus, and sensory and frontal cortices exhibited structural WM connectivity loss (p < 0.01). These data indicate early limbic system involvement even without GM atrophy. CONCLUSIONS Structural WM connectivity loss within the Papez circuit may precede and potentially predict GM atrophy in the temporal lobe of individuals with MCI+. These findings highlight the importance of investigating structural WM alterations in the prodromal phase of AD, which may inform diagnostic and therapeutic strategies in early AD.
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Affiliation(s)
| | - Michel J Grothe
- Reina Sofia Alzheimer Center, CIEN Foundation-ISCIII, Madrid, Spain
| | - Michel Thiebaut De Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France
| | - Filippo Sean Giorgi
- Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Via Roma 55, Pisa, 56126, Italy
- IRCCS Stella Maris Foundation, Pisa, Italy
| | - Andrea Vergallo
- Sorbonne University, Alzheimer Precision Medicine, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France
| | - Harald Hampel
- Sorbonne University, Alzheimer Precision Medicine, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France
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4
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Hanalioglu S, Bahadir S, Ozak AC, Yangi K, Mignucci-Jiménez G, Gurses ME, Fuentes A, Mathew E, Graham DT, Altug MY, Gok E, Turner GH, Lawton MT, Preul MC. Ultrahigh-resolution 7-Tesla anatomic magnetic resonance imaging and diffusion tensor imaging of ex vivo formalin-fixed human brainstem-cerebellum complex. Front Hum Neurosci 2024; 18:1484431. [PMID: 39664682 PMCID: PMC11631901 DOI: 10.3389/fnhum.2024.1484431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Accepted: 11/04/2024] [Indexed: 12/13/2024] Open
Abstract
Introduction Brain cross-sectional images, tractography, and segmentation are valuable resources for neuroanatomical education and research but are also crucial for neurosurgical planning that may improve outcomes in cerebellar and brainstem interventions. Although ultrahigh-resolution 7-Tesla (7T) magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) reveal such structural brain details in living or fresh unpreserved brain tissue, imaging standard formalin-preserved cadaveric brain specimens often used for neurosurgical anatomic studies has proven difficult. This study sought to develop a practical protocol to provide anatomic information and tractography results of an ex vivo human brainstem-cerebellum specimen. Materials and methods A protocol was developed for specimen preparation and 7T MRI with image postprocessing on a combined brainstem-cerebellum specimen obtained from an 85-year-old male cadaver with a postmortem interval of 1 week that was stored in formalin for 6 months. Anatomic image series were acquired for detailed views and diffusion tractography to map neural pathways and segment major anatomic structures within the brainstem and cerebellum. Results Complex white matter tracts were visualized with high-precision segmentation of crucial brainstem structures, delineating the brainstem-cerebellum and mesencephalic-dentate connectivity, including the Guillain-Mollaret triangle. Tractography and fractional anisotropy mapping revealed the complexities of white matter fiber pathways, including the superior, middle, and inferior cerebellar peduncles and visible decussating fibers. 3-dimensional (3D) reconstruction and quantitative and qualitative analyses verified the anatomical precision of the imaging relative to a standard brain space. Discussion This novel imaging protocol successfully captured the intricate 3D architecture of the brainstem-cerebellum network. The protocol, unique in several respects (including tissue preservation and rehydration times, choice of solutions, preferred sequences, voxel sizes, and diffusion directions) aimed to balance high resolution and practical scan times. This approach provided detailed neuroanatomical imaging while avoiding impractically long scan times. The extended postmortem and fixation intervals did not compromise the diffusion imaging quality. Moreover, the combination of time efficiency and ultrahigh-resolution imaging results makes this protocol a strong candidate for optimal use in detailed neuroanatomical studies, particularly in presurgical trajectory planning.
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Affiliation(s)
- Sahin Hanalioglu
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
- Department of Neurosurgery, Hacettepe University, Ankara, Türkiye
| | - Siyar Bahadir
- Department of Neurosurgery, Hacettepe University, Ankara, Türkiye
| | - Ahmet C. Ozak
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
- Department of Neurosurgery, Akdeniz University, Antalya, Türkiye
| | - Kivanc Yangi
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
- Department of Neurosurgery, Turkish Republic Ministry of Health, University of Health Sciences, Prof. Dr. Cemil Tascioglu City Hospital, Istanbul, Türkiye
| | - Giancarlo Mignucci-Jiménez
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
| | - Muhammet Enes Gurses
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
| | - Alberto Fuentes
- Neuroimaging Innovation Center, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Ethan Mathew
- Neuroimaging Innovation Center, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Dakota T. Graham
- Thurston Innovation Center, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | | | - Egemen Gok
- Department of Neurosurgery, Hacettepe University, Ankara, Türkiye
| | - Gregory H. Turner
- Center for In Vivo Imaging and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Michael T. Lawton
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
| | - Mark C. Preul
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
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Castro P, Luppi A, Tagliazucchi E, Perl YS, Naci L, Owen AM, Sitt JD, Destexhe A, Cofré R. Dynamical structure-function correlations provide robust and generalizable signatures of consciousness in humans. Commun Biol 2024; 7:1224. [PMID: 39349600 PMCID: PMC11443142 DOI: 10.1038/s42003-024-06858-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 09/06/2024] [Indexed: 10/04/2024] Open
Abstract
Resting-state functional magnetic resonance imaging evolves through a repertoire of functional connectivity patterns which might reflect ongoing cognition, as well as the contents of conscious awareness. We investigated whether the dynamic exploration of these states can provide robust and generalizable markers for the state of consciousness in human participants, across loss of consciousness induced by general anaesthesia or slow wave sleep. By clustering transient states of functional connectivity, we demonstrated that brain activity during unconsciousness is dominated by a recurrent pattern primarily mediated by structural connectivity and with a reduced capacity to transition to other patterns. Our results provide evidence supporting the pronounced differences between conscious and unconscious brain states in terms of whole-brain dynamics; in particular, the maintenance of rich brain dynamics measured by entropy is a critical aspect of conscious awareness. Collectively, our results may have significant implications for our understanding of consciousness and the neural basis of human awareness, as well as for the discovery of robust signatures of consciousness that are generalizable among different brain conditions.
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Affiliation(s)
- Pablo Castro
- Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, Gif-sur-Yvette, France
| | - Andrea Luppi
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Enzo Tagliazucchi
- Buenos Aires Physics Institute and Physics Department, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Yonatan S Perl
- Buenos Aires Physics Institute and Physics Department, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, Paris, France
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Lorina Naci
- Trinity College Institute of Neuroscience Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Adrian M Owen
- Departments of Physiology and Pharmacology and Psychology, Western University, London, Canada
| | - Jacobo D Sitt
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, Paris, France
| | - Alain Destexhe
- Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France.
| | - Rodrigo Cofré
- Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France.
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Luppi AI, Singleton SP, Hansen JY, Jamison KW, Bzdok D, Kuceyeski A, Betzel RF, Misic B. Contributions of network structure, chemoarchitecture and diagnostic categories to transitions between cognitive topographies. Nat Biomed Eng 2024; 8:1142-1161. [PMID: 39103509 PMCID: PMC11410673 DOI: 10.1038/s41551-024-01242-2] [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: 03/21/2023] [Accepted: 07/02/2024] [Indexed: 08/07/2024]
Abstract
The mechanisms linking the brain's network structure to cognitively relevant activation patterns remain largely unknown. Here, by leveraging principles of network control, we show how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic database. Specifically, we systematically integrated large-scale multimodal neuroimaging data from functional magnetic resonance imaging, diffusion tractography, cortical morphometry and positron emission tomography to simulate how anatomically guided transitions between cognitive states can be reshaped by neurotransmitter engagement or by changes in cortical thickness. Our model incorporates neurotransmitter-receptor density maps (18 receptors and transporters) and maps of cortical thickness pertaining to a wide range of mental health, neurodegenerative, psychiatric and neurodevelopmental diagnostic categories (17,000 patients and 22,000 controls). The results provide a comprehensive look-up table charting how brain network organization and chemoarchitecture interact to manifest different cognitive topographies, and establish a principled foundation for the systematic identification of ways to promote selective transitions between cognitive topographies.
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Affiliation(s)
- Andrea I Luppi
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
| | - S Parker Singleton
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Keith W Jamison
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Danilo Bzdok
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- MILA, Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Richard F Betzel
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Wang MB, Rahmani F, Benzinger TLS, Raji CA. Edge Density Imaging Identifies White Matter Biomarkers of Late-Life Obesity and Cognition. Aging Dis 2024; 15:1899-1912. [PMID: 37196133 PMCID: PMC11272213 DOI: 10.14336/ad.2022.1210] [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: 08/13/2022] [Accepted: 12/10/2022] [Indexed: 05/19/2023] Open
Abstract
Alzheimer disease (AD) and obesity are related to disruptions in the white matter (WM) connectome. We examined the link between the WM connectome and obesity and AD through edge-density imaging/index (EDI), a tractography-based method that characterizes the anatomical embedding of tractography connections. A total of 60 participants, 30 known to convert from normal cognition or mild-cognitive impairment to AD within a minimum of 24 months of follow up, were selected from the Alzheimer disease Neuroimaging Initiative (ADNI). Diffusion-weighted MR images from the baseline scans were used to extract fractional anisotropy (FA) and EDI maps that were subsequently averaged using deterministic WM tractography based on the Desikan-Killiany atlas. Multiple linear and logistic regression analysis were used to identify the weighted sum of tract-specific FA or EDI indices that maximized correlation to body-mass-index (BMI) or conversion to AD. Participants from the Open Access Series of Imaging Studies (OASIS) were used as an independent validation for the BMI findings. The edge-density rich, periventricular, commissural and projection fibers were among the most important WM tracts linking BMI to FA as well as to EDI. WM fibers that contributed significantly to the regression model related to BMI overlapped with those that predicted conversion; specifically in the frontopontine, corticostriatal, and optic radiation pathways. These results were replicated by testing the tract-specific coefficients found using ADNI in the OASIS-4 dataset. WM mapping with EDI enables identification of an abnormal connectome implicated in both obesity and conversion to AD.
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Affiliation(s)
- Maxwell Bond Wang
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.
- Medical Scientist Training Program, University of Pittsburgh/Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, Missouri, USA.
| | - Tammie L. S Benzinger
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, Missouri, USA.
| | - Cyrus A Raji
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, Missouri, USA.
- Department of Neurology, Washington University in Saint Louis, St. Louis, Missouri, USA
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8
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Liu H, Hua H, Kang T. White matter alterations predict outcomes of comprehensive behavioral intervention for tics in children with Tourette syndrome: A diffusion MRI study. J Psychiatr Res 2024; 175:418-424. [PMID: 38781676 DOI: 10.1016/j.jpsychires.2024.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 04/15/2024] [Accepted: 05/02/2024] [Indexed: 05/25/2024]
Abstract
AIM Tourette syndrome (TS) is a neurodevelopmental disorder that cause sudden uncontrolled rapid and repeated vocal sounds or movements called tics. Herein, diffusion magnetic resonance imaging (dMRI) connectometry was implemented to evaluate the white matter connectivity differences among TS patients. METHODS A total of 63 TS and 77 typically developed (TD) individuals were enrolled in the present study. dMRI connectometry was utilized to identify differences in connectivity patterns of white matter tracts in TS patients based on quantitative anisotropy (QA). QA was compared between TS and TD patients and correlated with severity scores such as Yale Global Tic Severity Scale (YGTSS) and Premonitory Urge for Tics Scale (PUTS). RESULTS Higher white matter connectivity of corpus callosum and bilateral cingulum as well as lower connectivity of corticothalamic and corticostriatal pathways were evident in TS relative to TD. The baseline YGTSS motor, YGTSS total, and PUTS were negatively correlated with corticostriatal pathway, corticothalamic pathway, and bilateral cingulum integrity, respectively. The changes in tic severity scores were also positively correlated with alterations in the white matter integrity of these brain regions following behavioral therapy. CONCLUSION Patients with TS have several abnormalities in their white matter microstructure particularly in the cortico-striato-thalamo-cortical (CSTC) circuit, correlated with the severity of the disease. Besides, the post-behavioral therapy changes in the white matter integrity of these regions are demonstrated as response predictors.
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Affiliation(s)
- Huiqin Liu
- Department of Neurology, Shijiazhuang People's Hospital, No. 365 Jianhua South Street, Yuhua District, Shijiazhuang, 050030, China
| | - Hongning Hua
- Department of Emergency Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Tian Kang
- Department of Pediatrics, Shijiazhuang People's Hospital, No. 365 Jianhua South Street, Yuhua District, Shijiazhuang, 050030, China.
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9
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Luppi AI, Olbrich E, Finn C, Suárez LE, Rosas FE, Mediano PA, Jost J. Quantifying synergy and redundancy between networks. CELL REPORTS. PHYSICAL SCIENCE 2024; 5:101892. [PMID: 38720789 PMCID: PMC11077508 DOI: 10.1016/j.xcrp.2024.101892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/18/2024] [Accepted: 03/01/2024] [Indexed: 05/12/2024]
Abstract
Understanding how different networks relate to each other is key for understanding complex systems. We introduce an intuitive yet powerful framework to disentangle different ways in which networks can be (dis)similar and complementary to each other. We decompose the shortest paths between nodes as uniquely contributed by one source network, or redundantly by either, or synergistically by both together. Our approach considers the networks' full topology, providing insights at multiple levels of resolution: from global statistics to individual paths. Our framework is widely applicable across scientific domains, from public transport to brain networks. In humans and 124 other species, we demonstrate the prevalence of unique contributions by long-range white-matter fibers in structural brain networks. Across species, efficient communication also relies on significantly greater synergy between long-range and short-range fibers than expected by chance. Our framework could find applications for designing network systems or evaluating existing ones.
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Affiliation(s)
- Andrea I. Luppi
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- St John’s College, University of Cambridge, Cambridge, UK
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Eckehard Olbrich
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
| | - Conor Finn
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
| | - Laura E. Suárez
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Fernando E. Rosas
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
- Department of Informatics, University of Sussex, Brighton, UK
- Centre for Complexity Science, Imperial College London, London, UK
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | | | - Jürgen Jost
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
- ScaDS.AI, Leipzig University, Leipzig, Germany
- Santa Fe Institute, Santa Fe, NM, USA
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10
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Luppi AI, Golkowski D, Ranft A, Ilg R, Jordan D, Bzdok D, Owen AM, Naci L, Stamatakis EA, Amico E, Misic B. General anaesthesia reduces the uniqueness of brain connectivity across individuals and across species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.08.566332. [PMID: 38014199 PMCID: PMC10680788 DOI: 10.1101/2023.11.08.566332] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The human brain is characterised by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain: both with respect to the brains of other individuals, and the brains of another species. We report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organised: it co-localises with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol, and reversed upon recovery. Providing convergent evidence, we show that under anaesthesia the functional connectivity of the human brain becomes more similar to the macaque brain. Finally, anaesthesia diminishes the match between spontaneous brain activity and meta-analytic brain patterns aggregated from the NeuroSynth engine. Collectively, the present results reveal that anaesthetised human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.
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Affiliation(s)
- Andrea I Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Daniel Golkowski
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Rudiger Ilg
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- Asklepios Clinic, Department of Neurology, Bad Tolz, Germany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- MILA, Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience (WIN), Western University, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Emmanuel A Stamatakis
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Enrico Amico
- Neuro-X Institute, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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11
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Sinha N, Duncan JS, Diehl B, Chowdhury FA, de Tisi J, Miserocchi A, McEvoy AW, Davis KA, Vos SB, Winston GP, Wang Y, Taylor PN. Intracranial EEG Structure-Function Coupling and Seizure Outcomes After Epilepsy Surgery. Neurology 2023; 101:e1293-e1306. [PMID: 37652703 PMCID: PMC10558161 DOI: 10.1212/wnl.0000000000207661] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 06/02/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Surgery is an effective treatment for drug-resistant epilepsy, which modifies the brain's structure and networks to regulate seizure activity. Our objective was to examine the relationship between brain structure and function to determine the extent to which this relationship affects the success of the surgery in controlling seizures. We hypothesized that a stronger association between brain structure and function would lead to improved seizure control after surgery. METHODS We constructed functional and structural brain networks in patients with drug-resistant focal epilepsy by using presurgery functional data from intracranial EEG (iEEG) recordings, presurgery and postsurgery structural data from T1-weighted MRI, and presurgery diffusion-weighted MRI. We quantified the relationship (coupling) between structural and functional connectivity by using the Spearman rank correlation and analyzed this structure-function coupling at 2 spatial scales: (1) global iEEG network level and (2) individual iEEG electrode contacts using virtual surgeries. We retrospectively predicted postoperative seizure freedom by incorporating the structure-function connectivity coupling metrics and routine clinical variables into a cross-validated predictive model. RESULTS We conducted a retrospective analysis on data from 39 patients who met our inclusion criteria. Brain areas implanted with iEEG electrodes had stronger structure-function coupling in seizure-free patients compared with those with seizure recurrence (p = 0.002, d = 0.76, area under the receiver operating characteristic curve [AUC] = 0.78 [95% CI 0.62-0.93]). Virtual surgeries on brain areas that resulted in stronger structure-function coupling of the remaining network were associated with seizure-free outcomes (p = 0.007, d = 0.96, AUC = 0.73 [95% CI 0.58-0.89]). The combination of global and local structure-function coupling measures accurately predicted seizure outcomes with a cross-validated AUC of 0.81 (95% CI 0.67-0.94). These measures were complementary to other clinical variables and, when included for prediction, resulted in a cross-validated AUC of 0.91 (95% CI 0.82-1.0), accuracy of 92%, sensitivity of 93%, and specificity of 91%. DISCUSSION Our study showed that the strength of structure-function connectivity coupling may play a crucial role in determining the success of epilepsy surgery. By quantitatively incorporating structure-function coupling measures and standard-of-care clinical variables into presurgical evaluations, we may be able to better localize epileptogenic tissue and select patients for epilepsy surgery. CLASSIFICATION OF EVIDENCE This is a Class IV retrospective case series showing that structure-function mapping may help determine the outcome from surgical resection for treatment-resistant focal epilepsy.
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Affiliation(s)
- Nishant Sinha
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada.
| | - John S Duncan
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Beate Diehl
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Fahmida A Chowdhury
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Jane de Tisi
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Anna Miserocchi
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Andrew William McEvoy
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Kathryn A Davis
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Sjoerd B Vos
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Gavin P Winston
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Yujiang Wang
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Peter Neal Taylor
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
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12
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Mosch B, Hagena V, Herpertz S, Diers M. Brain morphometric changes in fibromyalgia and the impact of psychometric and clinical factors: a volumetric and diffusion-tensor imaging study. Arthritis Res Ther 2023; 25:81. [PMID: 37208755 PMCID: PMC10197341 DOI: 10.1186/s13075-023-03064-0] [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: 12/08/2022] [Accepted: 05/07/2023] [Indexed: 05/21/2023] Open
Abstract
BACKGROUND Previous studies have repeatedly found distinct brain morphometric changes in patients with fibromyalgia (FM), mainly affecting gray and white matter abnormalities in areas related to sensory and affective pain processing. However, few studies have thus far linked different types of structural changes and not much is known about behavioral and clinical determinants that might influence the emergence and progression of such changes. METHODS We used voxel-based morphometry (VBM) and diffusion-tensor imaging (DTI) to detect regional patterns of (micro)structural gray (GM) and white matter (WM) alterations in 23 patients with FM compared to 21 healthy controls (HC), while considering the influence of demographic, psychometric, and clinical variables (age, symptom severity, pain duration, heat pain threshold, depression scores). RESULTS VBM and DTI revealed striking patterns of brain morphometric changes in FM patients. Bilateral middle temporal gyrus (MTG), parahippocampal gyrus, left dorsal anterior cingulate cortex (dACC), right putamen, right caudate nucleus, and left dorsolateral prefrontal cortex (DLPFC) showed significantly decreased GM volumes. In contrast, increased GM volume was observed in bilateral cerebellum and left thalamus. Beyond that, patients displayed microstructural changes of WM connectivity within the medial lemniscus, corpus callosum, and tracts surrounding and connecting the thalamus. Sensory-discriminative aspects of pain (pain severity, pain thresholds) primarily showed negative correlations with GM within bilateral putamen, pallidum, right midcingulate cortex (MCC), and multiple thalamic substructures, whereas the chronicity of pain was negatively correlated with GM volumes within right insular cortex and left rolandic operculum. Affective-motivational aspects of pain (depressive mood, general activity) were related to GM and FA values within bilateral putamen and thalamus. CONCLUSIONS Our results suggest a variety of distinct structural brain changes in FM, particularly affecting areas involved in pain and emotion processing such as the thalamus, putamen, and insula.
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Affiliation(s)
- Benjamin Mosch
- Department of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr University Bochum, Alexandrinenstraße 1-3, 44791, Bochum, Germany
| | - Verena Hagena
- Department of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr University Bochum, Alexandrinenstraße 1-3, 44791, Bochum, Germany
| | - Stephan Herpertz
- Department of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr University Bochum, Alexandrinenstraße 1-3, 44791, Bochum, Germany
| | - Martin Diers
- Department of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr University Bochum, Alexandrinenstraße 1-3, 44791, Bochum, Germany.
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13
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Schmithorst V, Ceschin R, Lee V, Wallace J, Sahel A, Chenevert TL, Parmar H, Berman JI, Vossough A, Qiu D, Kadom N, Grant PE, Gagoski B, LaViolette PS, Maheshwari M, Sleeper LA, Bellinger DC, Ilardi D, O’Neil S, Miller TA, Detterich J, Hill KD, Atz AM, Richmond ME, Cnota J, Mahle WT, Ghanayem NS, Gaynor JW, Goldberg CS, Newburger JW, Panigrahy A. Single Ventricle Reconstruction III: Brain Connectome and Neurodevelopmental Outcomes: Design, Recruitment, and Technical Challenges of a Multicenter, Observational Neuroimaging Study. Diagnostics (Basel) 2023; 13:1604. [PMID: 37174995 PMCID: PMC10178603 DOI: 10.3390/diagnostics13091604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 04/25/2023] [Accepted: 04/27/2023] [Indexed: 05/15/2023] Open
Abstract
Patients with hypoplastic left heart syndrome who have been palliated with the Fontan procedure are at risk for adverse neurodevelopmental outcomes, lower quality of life, and reduced employability. We describe the methods (including quality assurance and quality control protocols) and challenges of a multi-center observational ancillary study, SVRIII (Single Ventricle Reconstruction Trial) Brain Connectome. Our original goal was to obtain advanced neuroimaging (Diffusion Tensor Imaging and Resting-BOLD) in 140 SVR III participants and 100 healthy controls for brain connectome analyses. Linear regression and mediation statistical methods will be used to analyze associations of brain connectome measures with neurocognitive measures and clinical risk factors. Initial recruitment challenges occurred that were related to difficulties with: (1) coordinating brain MRI for participants already undergoing extensive testing in the parent study, and (2) recruiting healthy control subjects. The COVID-19 pandemic negatively affected enrollment late in the study. Enrollment challenges were addressed by: (1) adding additional study sites, (2) increasing the frequency of meetings with site coordinators, and (3) developing additional healthy control recruitment strategies, including using research registries and advertising the study to community-based groups. Technical challenges that emerged early in the study were related to the acquisition, harmonization, and transfer of neuroimages. These hurdles were successfully overcome with protocol modifications and frequent site visits that involved human and synthetic phantoms.
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Affiliation(s)
- Vanessa Schmithorst
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Floor 2, Pittsburgh, PA 15224, USA
| | - Rafael Ceschin
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Floor 2, Pittsburgh, PA 15224, USA
- Department of Biomedical Informatics, University of Pittsburgh School, 5607 Baum Blvd., Pittsburgh, PA 15206, USA
| | - Vincent Lee
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Floor 2, Pittsburgh, PA 15224, USA
| | - Julia Wallace
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Floor 2, Pittsburgh, PA 15224, USA
| | - Aurelia Sahel
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Floor 2, Pittsburgh, PA 15224, USA
| | - Thomas L. Chenevert
- Michigan Medicine Department of Radiology, University of Michigan, 1500 E Medical Center Dr., Ann Arbor, MI 48109, USA
| | - Hemant Parmar
- Michigan Medicine Department of Radiology, University of Michigan, 1500 E Medical Center Dr., Ann Arbor, MI 48109, USA
| | - Jeffrey I. Berman
- Department of Radiology, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Arastoo Vossough
- Department of Radiology, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Children’s Healthcare of Atlanta, Emory University, 1364 Clifton Rd, Atlanta, GA 30322, USA
| | - Nadja Kadom
- Department of Radiology and Imaging Sciences, Children’s Healthcare of Atlanta, Emory University, 1364 Clifton Rd, Atlanta, GA 30322, USA
| | - Patricia Ellen Grant
- Children’s Hospital Boston, Fetal-Neonatal Neuroimaging and Developmental Science Center (FNNDSC), 300 Longwood Avenue, Boston, MA 02115, USA
| | - Borjan Gagoski
- Department of Radiology, Children’s Hospital Boston, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Peter S. LaViolette
- Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Avenue, Milwaukee, WI 53226, USA
| | - Mohit Maheshwari
- Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Avenue, Milwaukee, WI 53226, USA
| | - Lynn A. Sleeper
- Department of Cardiology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
- Department of Pediatrics, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - David C. Bellinger
- Cardiac Neurodevelopmental Program, Department of Neurology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Dawn Ilardi
- Department of Neuropsychology, Children’s Healthcare of Atlanta, 1400 Tullie Road NE, Atlanta, GA 30329, USA
| | - Sharon O’Neil
- Children’s Hospital Los Angeles, Neuropsychology Core of the Saban Research Institute, 4661 Sunset Blvd., Los Angeles, CA 90027, USA
| | - Thomas A. Miller
- Division of Pediatric Cardiology, Department of Pediatrics, University of Utah School of Medicine, 30 N 1900 E, Salt Lake City, UT 84132, USA
| | - Jon Detterich
- Division of Pediatric Cardiology, Children’s Hospital Los Angeles, 4650 Sunset Blvd., Los Angeles, CA 90027, USA
| | - Kevin D. Hill
- Division of Pediatric Cardiology, Department of Pediatrics, Duke University School of Medicine, 7506 Hospital North, DUMC Box 3090, Durham, NC 27710, USA
| | - Andrew M. Atz
- Division of Pediatric Cardiology, Medical University of South Carolina, 96 Jonathan Lucas St. Ste. 601, MSC 617, Charleston, SC 29425, USA
| | - Marc E. Richmond
- Program for Pediatric Cardiomyopathy, Heart Failure, and Transplantation, New York-Presbyterian Morgan Stanley Children’s Hospital, 3959 Broadway MSCH North, 2nd Floor, New York, NY 10032, USA
| | - James Cnota
- Fetal Heart Program, Cincinnati Children’s, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
| | - William T. Mahle
- Division of Pediatric Cardiology, Children’s Healthcare of Atlanta, 1400 Tullie Rd NE Suite 630, Atlanta, GA 30329, USA
| | - Nancy S. Ghanayem
- Section of Pediatric Critical Care, Department of Pediatrics, Comer Children’s Hospital, University of Chicago Medicine, 5721 S. Maryland Avenue, Chicago, IL 60637, USA
- Department of Pediatrics, Medical College of Wisconsin Section of Pediatric Critical Care, 9000 W. Wisconsin Avenue MS 681, Milwaukee, WI 53226, USA
| | - J. William Gaynor
- Heart Failure and Transplant Program, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Caren S. Goldberg
- Department of Pediatrics, Division of Cardiology, C.S. Mott Children’s Hospital, 1540 E Hospital Dr #4204, Ann Arbor, MI 48109, USA
| | - Jane W. Newburger
- Department of Cardiology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Ashok Panigrahy
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Floor 2, Pittsburgh, PA 15224, USA
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14
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Schmithorst V, Ceschin R, Lee V, Wallace J, Sahel A, Chenevert T, Parmar H, Berman JI, Vossough A, Qiu D, Kadom N, Grant PE, Gagoski B, LaViolette P, Maheshwari M, Sleeper LA, Bellinger D, Ilardi D, O’Neil S, Miller TA, Detterich J, Hill KD, Atz AM, Richmond M, Cnota J, Mahle WT, Ghanayem N, Gaynor W, Goldberg CS, Newburger JW, Panigrahy A. Single Ventricle Reconstruction III: Brain Connectome and Neurodevelopmental Outcomes: Design, Recruitment, and Technical Challenges of a Multicenter, Observational Neuroimaging Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.12.23288433. [PMID: 37131744 PMCID: PMC10153324 DOI: 10.1101/2023.04.12.23288433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Patients with hypoplastic left heart syndrome who have been palliated with the Fontan procedure are at risk for adverse neurodevelopmental outcomes, lower quality of life, and reduced employability. We describe the methods (including quality assurance and quality control protocols) and challenges of a multi-center observational ancillary study, SVRIII (Single Ventricle Reconstruction Trial) Brain Connectome. Our original goal was to obtain advanced neuroimaging (Diffusion Tensor Imaging and Resting-BOLD) in 140 SVR III participants and 100 healthy controls for brain connectome analyses. Linear regression and mediation statistical methods will be used to analyze associations of brain connectome measures with neurocognitive measures and clinical risk factors. Initial recruitment challenges occurred related to difficulties with: 1) coordinating brain MRI for participants already undergoing extensive testing in the parent study, and 2) recruiting healthy control subjects. The COVID-19 pandemic negatively affected enrollment late in the study. Enrollment challenges were addressed by 1) adding additional study sites, 2) increasing the frequency of meetings with site coordinators and 3) developing additional healthy control recruitment strategies, including using research registries and advertising the study to community-based groups. Technical challenges that emerged early in the study were related to the acquisition, harmonization, and transfer of neuroimages. These hurdles were successfully overcome with protocol modifications and frequent site visits that involved human and synthetic phantoms. Trial registration number ClinicalTrials.gov Registration Number: NCT02692443.
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Affiliation(s)
- Vanessa Schmithorst
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave, Floor 2, Pittsburgh, PA 15224 USA
| | - Rafael Ceschin
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave, Floor 2, Pittsburgh, PA 15224 USA
- Department of Biomedical Informatics, University of Pittsburgh School, 5607 Baum Blvd, Pittsburgh, PA 15206-3701 USA
| | - Vince Lee
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave, Floor 2, Pittsburgh, PA 15224 USA
| | - Julia Wallace
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave, Floor 2, Pittsburgh, PA 15224 USA
| | - Aurelia Sahel
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave, Floor 2, Pittsburgh, PA 15224 USA
| | - Thomas Chenevert
- Department of Radiology, Michigan Medicine, University of Michigan, University of Michigan, 1500 E Medical Center Dr, Ann Arbor, MI 48109 USA
| | - Hemant Parmar
- Department of Radiology, Michigan Medicine, University of Michigan, University of Michigan, 1500 E Medical Center Dr, Ann Arbor, MI 48109 USA
| | - Jeffrey I. Berman
- Department of Radiology, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, USA
| | - Arastoo Vossough
- Department of Radiology, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, USA
| | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Children’s Healthcare of Atlanta, Emory University, 1364 Clifton Rd, Atlanta, GA 30322 USA
| | - Nadja Kadom
- Department of Radiology and Imaging Sciences, Children’s Healthcare of Atlanta, Emory University, 1364 Clifton Rd, Atlanta, GA 30322 USA
| | - Patricia Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Children’s Hospital Boston, 300 Longwood Avenue, Boston, MA 02115 USA
| | - Borjan Gagoski
- Department of Radiology, Children’s Hospital Boston, 300 Longwood Ave, Boston, MA 02115 USA
| | - Peter LaViolette
- Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI 53226 USA
| | - Mohit Maheshwari
- Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI 53226 USA
| | - Lynn A. Sleeper
- Department of Cardiology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115
- Department of Pediatrics, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115 USA
| | - David Bellinger
- Cardiac Neurodevelopmental Program, Department of Neurology, Boston, Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115 USA
| | - Dawn Ilardi
- Department of Neuropsychology, Children’s Healthcare of Atlanta, 1400 Tullie Road NE, Atlanta, GA 30329
| | - Sharon O’Neil
- Neuropsychology Core of the Saban Research Institute, Children’s Hospital Los Angeles, 4661 Sunset Blvd., Los Angeles, CA 90027 USA
| | - Thomas A. Miller
- Division of Pediatric Cardiology, Department of Pediatrics, University of Utah, School of Medicine, 30 N 1900 E, Salt Lake City, UT 84132 USA
| | - Jon Detterich
- Division of Pediatric Cardiology, Children’s Hospital Los Angeles, 4650 Sunset Blvd, Los Angeles, CA 90027 USA
| | - Kevin D. Hill
- Division of Pediatric Cardiology, Department of Pediatrics, Duke University, School of Medicine, 7506 Hospital North, DUMC Box 3090, Durham, NC 27710 USA
| | - Andrew M. Atz
- Division of Pediatric Cardiology, Medical University of South Carolina, 96 Jonathan Lucas St. Ste. 601, MSC 617, Charleston, SC 29425 USA
| | - Marc Richmond
- Program for Pediatric Cardiomyopathy, Heart Failure, and Transplantation, New York-Presbyterian Morgan Stanley Children’s Hospital, 3959 Broadway MSCH North, 2 Floor, New York, NY 10032 USA
| | - James Cnota
- Fetal Heart Program, Cincinnati Children’s, 3333 Burnet Avenue, Cincinnati, Ohio 45229-3026 USA
| | - William T. Mahle
- Division of Pediatric Cardiology, Children’s Healthcare of Atlanta, 1400 Tullie Rd NE Suite 630, Atlanta, GA 30329
| | - Nancy Ghanayem
- Section of Pediatric Critical Care, Department of Pediatrics, University of Chicago Medicine, Comer Children’s Hospital, 5721 S. Maryland Ave., Chicago, IL 60637 USA
- Section of Pediatric Critical Care, Department of Pediatrics, Medical College of Wisconsin, 9000 W. Wisconsin Ave. MS 681, Milwaukee, WI 53226 USA
| | - William Gaynor
- Heart Failure and Transplant Program, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Caren S. Goldberg
- Department of Pediatrics, Division of Cardiology, C.S. Mott Children’s Hospital, 1540 E Hospital Dr #4204, Ann Arbor, MI 48109 USA
| | - Jane W. Newburger
- Department of Cardiology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115
| | - Ashok Panigrahy
- Department of Radiology, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave, Floor 2, Pittsburgh, PA 15224 USA
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15
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Luppi AI, Mediano PAM, Rosas FE, Allanson J, Pickard JD, Williams GB, Craig MM, Finoia P, Peattie ARD, Coppola P, Menon DK, Bor D, Stamatakis EA. Reduced emergent character of neural dynamics in patients with a disrupted connectome. Neuroimage 2023; 269:119926. [PMID: 36740030 PMCID: PMC9989666 DOI: 10.1016/j.neuroimage.2023.119926] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 01/23/2023] [Accepted: 02/02/2023] [Indexed: 02/05/2023] Open
Abstract
High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Leverhulme Centre for the Future of Intelligence, Cambridge, UK; The Alan Turing Institute, London, UK.
| | - Pedro A M Mediano
- Department of Computing, Imperial College London, London, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Fernando E Rosas
- Department of Brain Science, Center for Psychedelic Research, Imperial College London, London, UK; Data Science Institute, Imperial College London, London, UK; Centre for Complexity Science, Imperial College London, London, UK; Center for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK; Department of Informatics, University of Sussex, Brighton, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Department of Neurosciences, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Paola Finoia
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Alexander R D Peattie
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, UK; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Daniel Bor
- Department of Psychology, University of Cambridge, Cambridge, UK; Department of Psychology, Queen Mary University of London, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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16
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Mallahzadeh A, Shafie M, Tahvilian M, Sadeghi M, Moslemian G, Barzin P, Bemanalizadeh M, Mayeli M, Aarabi MH. White matter tracts alterations underpinning reward and conflict processing. J Affect Disord 2023; 331:251-258. [PMID: 36958490 DOI: 10.1016/j.jad.2023.03.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/10/2023] [Accepted: 03/20/2023] [Indexed: 03/25/2023]
Abstract
BACKGROUND Reinforcement sensitivity theory (RST) is proposed as a neurobiological system that eventually led to emotion and motivation-based constructs of personality. Traditionally segmented into the behavioral activation system (BAS) and the behavioral inhibition system (BIS), RST is commonly used to describe personality and behavior. Although there have been studies linking gray matter alterations with BIS/BAS subscales, the role of white matter (WM) alterations is yet controversial. We aimed to investigate the specific WM tracts associated with BIS/BAS scores. METHODS 220 healthy participants (mean age = 39.14 ± 20.23, 80 (35.7 %) females) were evaluated using the BIS/BAS questionnaire from the LEMON database. Diffusion MRI connectometry (DMRI) was used to investigate the WM correlates of BIS/BAS subscales in each gender group. Multiple regression models with the covariates of age, handedness, and education were fitted to address the correlation of local connectomes with BIS/BAS components. RESULTS DMRI connectometry revealed that the quantitative anisotropy (QA) value of the splenium of the corpus callosum, right cerebellum, middle cerebellar peduncle, and superior cerebellar peduncle, had a significant negative correlation with each BIS/BAS subscale. In contrast, the QA value in the body of the corpus callosum and bilateral cingulum showed a positive correlation with BIS/BAS subscales. CONCLUSION The connectivity of WM in certain tracts may contribute to behavioral activation and inhibition. This finding expands the findings on the neural networks associated with risk-taking and reward-seeking behaviors.
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Affiliation(s)
- Arashk Mallahzadeh
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahan Shafie
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahdi Tahvilian
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadeghi
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Golsa Moslemian
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Pouria Barzin
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Bemanalizadeh
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahsa Mayeli
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Iranian Center of Neurological Research, Imam Khomeini Hospital Complex, Tehran, Iran.
| | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
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17
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Luppi AI, Singleton SP, Hansen JY, Bzdok D, Kuceyeski A, Betzel RF, Misic B. Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532981. [PMID: 36993597 PMCID: PMC10055141 DOI: 10.1101/2023.03.16.532981] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain's network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.
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Affiliation(s)
- Andrea I. Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | - Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- MILA, Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, U.S.A
| | - Richard F. Betzel
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, U.S.A
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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18
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Sinaeifar Z, Mayeli M, Shafie M, Pooyan A, Cattarinussi G, Aarabi MH, Sambataro F. Trait anger representation in microstructural white matter tracts: A diffusion MRI study. J Affect Disord 2023; 322:249-257. [PMID: 36368424 DOI: 10.1016/j.jad.2022.11.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 08/31/2022] [Accepted: 11/06/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Understanding the microstructure of the brain that underlies emotions is of pivotal importance for psychology and psychiatry. Herein, we investigated white matter (WM) tracts associated with anger using the diffusion magnetic resonance imaging (DMRI) connectometry approach while exploring potential sex differences. METHODS 225 healthy participants from the LEMON database were evaluated using the State-Trait Anger Expression Inventory (STAXI). WM images were prepared and analyzed with DMRI. Multiple regression models were fitted to address the correlation of local connectomes with STAXI components with age and handedness as covariates. RESULTS There were no statistically significant differences in state anger and trait anger between males and females (p = 0.55 and 0.30, respectively). DMRI connectometry revealed that quantitative anisotropy (QA) values in the bilateral corticospinal tract (CST), splenium of corpus callosum (SCC), middle cerebellar peduncle, left inferior cerebellar peduncle, left cingulum, and left fornix were negatively correlated with trait anger and trait anger temperament (TAT) in males. In contrast, the QA values in the bilateral CST and SCC showed a positive correlation with trait anger and TAT in females, which, however, did not reach statistical significance. LIMITATIONS The cross-sectional design and self-reported measures of anger limit the generalizability of our results. CONCLUSIONS This is the first DMRI connectometry study to investigate WM circuits involved in anger. We found that the pathways associated with the limbic system and movement-related regions were involved in trait anger and anger expression in men, while no brain pathways showed a significant relationship with anger in women.
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Affiliation(s)
- Zeinab Sinaeifar
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahsa Mayeli
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahdieh Shafie
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Atefe Pooyan
- Department of Radiology, University of Washington, Seattle, USA
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy.
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19
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Moss HG, Benitez A, Jensen JH. Optimized rectification of fiber orientation density function with background threshold. Magn Reson Imaging 2023; 95:80-89. [PMID: 36368495 PMCID: PMC9695117 DOI: 10.1016/j.mri.2022.11.001] [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: 09/07/2022] [Revised: 10/27/2022] [Accepted: 11/03/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To describe an optimized fiber orientation density function (fODF) rectification procedure that removes negative values and absorbs all features below a specified threshold into a constant background. THEORY AND METHODS The fODF for a white matter imaging voxel describes the angular density of axons. Because of signal noise and Gibbs ringing, fODFs estimated with diffusion MRI may take on unphysical negative values in some directions and contain spurious peaks. In order to suppress such artifacts, an fODF rectification procedure is proposed that both eliminates all negative values and incorporates all features below a specified threshold, η, into a constant background while at the same time minimizing the mean square deviation from the original, unrectified fODF. Calculating this fODF is straightforward, and the directions and shapes of peaks not absorbed into the background are preserved. The rectification method is illustrated for an analytic fODF model and for experimental diffusion MRI data obtained in healthy human brain, with the original fODFs being obtained from fiber ball imaging. RESULTS Examples of optimal rectified fODFs are given for three choices of the background threshold referred to as minimal rectification (η = 0), average-level rectification (η ≈ 0.08), and fractional-anisotropy-axonal-based rectification (η ≈ 0.1). As η is increased, artifacts and other small features are more strongly suppressed, but the major fODF peaks are largely unaffected for the range of η values illustrated by these three alternatives. CONCLUSION Artifactual features of fODFs estimated with diffusion MRI can be effectively suppressed by applying the proposed optimized rectification procedure. Since it minimizes fODF distortion in the mean square sense, it may be useful in the study of how fODF fine structure is affected by aging and disease.
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Affiliation(s)
- Hunter G Moss
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States of America; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States of America
| | - Andreana Benitez
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States of America; Department of Neurology, Medical University of South Carolina, Charleston, SC, United States of America
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States of America; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States of America; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States of America.
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20
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Coppola P, Allanson J, Naci L, Adapa R, Finoia P, Williams GB, Pickard JD, Owen AM, Menon DK, Stamatakis EA. The complexity of the stream of consciousness. Commun Biol 2022; 5:1173. [PMID: 36329176 PMCID: PMC9633704 DOI: 10.1038/s42003-022-04109-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
Typical consciousness can be defined as an individual-specific stream of experiences. Modern consciousness research on dynamic functional connectivity uses clustering techniques to create common bases on which to compare different individuals. We propose an alternative approach by combining modern theories of consciousness and insights arising from phenomenology and dynamical systems theory. This approach enables a representation of an individual's connectivity dynamics in an intrinsically-defined, individual-specific landscape. Given the wealth of evidence relating functional connectivity to experiential states, we assume this landscape is a proxy measure of an individual's stream of consciousness. By investigating the properties of this landscape in individuals in different states of consciousness, we show that consciousness is associated with short term transitions that are less predictable, quicker, but, on average, more constant. We also show that temporally-specific connectivity states are less easily describable by network patterns that are distant in time, suggesting a richer space of possible states. We show that the cortex, cerebellum and subcortex all display consciousness-relevant dynamics and discuss the implication of our results in forming a point of contact between dynamical systems interpretations and phenomenology.
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Affiliation(s)
- Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, UK
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Ram Adapa
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Adrian M Owen
- The Brain and Mind Institute, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, ON, Canada
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
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21
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Tang R, Elman JA, Franz CE, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Kremen WS. Longitudinal association of executive function and structural network controllability in the aging brain. GeroScience 2022; 45:837-849. [PMID: 36269506 PMCID: PMC9886719 DOI: 10.1007/s11357-022-00676-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/12/2022] [Indexed: 02/03/2023] Open
Abstract
Executive function encompasses effortful cognitive processes that are particularly susceptible to aging. Functional brain networks supporting executive function-such as the frontoparietal control network and the multiple demand system-have been extensively investigated. However, it remains unclear how structural networks facilitate and constrain the dynamics of functional networks to contribute to aging-related executive function declines. We examined whether changes in structural network modal controllability-a network's ability to facilitate effortful brain state transitions that support cognitive functions-are associated with changes in executive function cross-sectionally and longitudinally. Diffusion-weighted imaging and neuropsychological testing were conducted at two time points (Time 1: ages 56 to 66, N = 172; Time 2: ages 61 to 70, N = 267) in community-dwelling men from the Vietnam Era Twin Study of Aging. An executive function factor score was computed from six neuropsychological tasks. Structural networks constructed from white matter connectivity were used to estimate modal controllability in control network and multiple demand system. We showed that higher modal controllability in control network and multiple demand system was associated with better executive function at Time 2, after controlling for age, young adult general cognitive ability, and physical health status. Moreover, changes in executive function over a period of 5 to 6 years (Time 1-Time 2, N = 105) were associated with changes in modal controllability of the multiple demand system and weakly in the control network over the same time period. These findings suggest that changes in the ability of structural brain networks in facilitating effortful brain state transitions may be a key neural mechanism underlying aging-related executive function declines and cognitive aging.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA. .,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
| | - Jeremy A. Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Carol E. Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Anders M. Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093 USA ,Department of Neurosciences, University of California San Diego, La Jolla, CA 92093 USA
| | - Lisa T. Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA 92093 USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Department of Radiology, University of California San Diego, La Jolla, CA 92093 USA
| | - Donald J. Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093 USA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02212 USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Olivia K. Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - William S. Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
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22
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Singleton SP, Luppi AI, Carhart-Harris RL, Cruzat J, Roseman L, Nutt DJ, Deco G, Kringelbach ML, Stamatakis EA, Kuceyeski A. Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain's control energy landscape. Nat Commun 2022; 13:5812. [PMID: 36192411 PMCID: PMC9530221 DOI: 10.1038/s41467-022-33578-1] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/22/2022] [Indexed: 11/09/2022] Open
Abstract
Psychedelics including lysergic acid diethylamide (LSD) and psilocybin temporarily alter subjective experience through their neurochemical effects. Serotonin 2a (5-HT2a) receptor agonism by these compounds is associated with more diverse (entropic) brain activity. We postulate that this increase in entropy may arise in part from a flattening of the brain's control energy landscape, which can be observed using network control theory to quantify the energy required to transition between recurrent brain states. Using brain states derived from existing functional magnetic resonance imaging (fMRI) datasets, we show that LSD and psilocybin reduce control energy required for brain state transitions compared to placebo. Furthermore, across individuals, reduction in control energy correlates with more frequent state transitions and increased entropy of brain state dynamics. Through network control analysis that incorporates the spatial distribution of 5-HT2a receptors (obtained from publicly available positron emission tomography (PET) data under non-drug conditions), we demonstrate an association between the 5-HT2a receptor and reduced control energy. Our findings provide evidence that 5-HT2a receptor agonist compounds allow for more facile state transitions and more temporally diverse brain activity. More broadly, we demonstrate that receptor-informed network control theory can model the impact of neuropharmacological manipulation on brain activity dynamics.
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Affiliation(s)
- S Parker Singleton
- Department of Computational Biology, Cornell University, Ithaca, NY, USA.
| | - Andrea I Luppi
- Division of Anesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
- Psychedelics Division, Neuroscape, University of California San Francisco, San Francisco, CA, USA
| | - Josephine Cruzat
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain
| | - Leor Roseman
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
| | - David J Nutt
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC, Australia
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center of Music in the Brain (MIB), Clinical Medicine, Aarhus University, Aarhus, Denmark
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - Emmanuel A Stamatakis
- Division of Anesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Amy Kuceyeski
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
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23
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Seyedmirzaei H, Shafie M, Kargar A, Golbahari A, Bijarchian M, Ahmadi S, Shahmohammadi A, Sadeghi M, Aarabi MH, Mayeli M. White matter tracts associated with alexithymia and emotion regulation: A diffusion MRI study. J Affect Disord 2022; 314:271-280. [PMID: 35878842 DOI: 10.1016/j.jad.2022.07.039] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/27/2022] [Accepted: 07/17/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND Alexithymia is a cognitive-affective impairment, suggested to be associated with emotion regulation. Herein, we investigated white matter (WM) tracts with Diffusion Magnetic Resonance Imaging (DMRI) connectometry approach using quantitative anisotropy (QA) tractography to discover possible associations between the emotion identification and regulation patterns and WM tracts. METHODS DMRI data were acquired from 218 healthy subjects aging 39.15 ± 20.19 who filled the Toronto Alexithymia Scale (TAS) and emotion regulation questionnaire (ERQ) from the LEMON dataset. Connectometry analysis was applied on WM tracts in DMRI images. RESULTS DMRI connectometry analysis revealed a significant correlation between TAS identification score and increased microstructural connectivity in WM pathways, including the body of corpus callosum (CC), bilateral fornix, and left arcuate fasciculus (AF) in males (FDR = 0.028), and corticospinal and cingulum tracts in females (FDR = 0.026). Furthermore, we found a significant positive correlation between overall TAS score and fornix properties in men (FDR = 0.026) and corticospinal tracts in women (FDR = 0.028). Middle cerebellar peduncle negatively correlated with describing emotion (FDR = 0.025) and the splenium of the CC and corticospinal tracts negatively correlated with this subscale (FDR = 0.049) in male group. However, the splenium of the CC, corticospinal tracts, and left AF positively associated with this subscale (FDR = 0.029). The splenium of the CC was negatively related to externally-oriented thinking among men (FDR = 0.038). Our results showed marginally associations between ERQ and similar WM tracts. CONCLUSION Certain WM microstructures significantly correlate with emotion identification and regulation. These tracts are associated with specific somatosensory areas, language processing areas, and limbic area.
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Affiliation(s)
- Homa Seyedmirzaei
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahan Shafie
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Iranian Center of Neurological Research, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Amirhosein Kargar
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Golbahari
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Motahareh Bijarchian
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Sepide Ahmadi
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Alireza Shahmohammadi
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadeghi
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy.
| | - Mahsa Mayeli
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Iranian Center of Neurological Research, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
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24
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Wan X, Xiao Y, Liu Z. Diffusion spectrum imaging of patients with middle cerebral artery stenosis. Neuroimage Clin 2022; 36:103133. [PMID: 35973283 PMCID: PMC9400121 DOI: 10.1016/j.nicl.2022.103133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/11/2022] [Accepted: 07/27/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE We aimed to detect microstructural changes in the brains of patients with unilateral middle cerebral artery (MCA) stenosis and to assess the integrity of the fiber structure and the small-world networks using diffusion spectrum imaging (DSI). METHODS A total of 21 healthy controls and 48 patients with unilateral MCA stenosis underwent 3.0 T MRI examination using DSI technique. Differential tractography, diffusion connectometry, and structural networks were performed by using DSI software. The correlation between the stenosis and quantitative anisotropy (QA) were analyzed using multiple regression models in the correlation tractography. RESULTS Differential tractography analysis showed that the left or right MCA stenosis group had decreased fiber connectivity in the brain network compared with the control group. The correlation tractography analysis of the patients with MCA stenosis showed that QA was negatively correlated with stenosis in the bilateral arcuate fasciculus, bilateral corticostriatal and corticothalamic pathway, bilateral corticopontine and corticospinal tract, right superior longitudinal fasciculus, right cingulum, corpus callosum, and left frontal aslant tract. Statistically significant differences were shown between the MCA stenosis groups and control group in graph density, global efficiency, network path length, and rich club coefficient. CONCLUSION DSI revealed that stroke-free patients with unilateral MCA stenosis have a disrupted structural network and damaged white matter fibers. Furthermore, the fiber connection disruption is more severe in the ipsilateral hemisphere and less prominent in the contralateral hemisphere in patients with unilateral MCA stenosis. Therefore, microstructural impairment has happened to patients with unilateral MCA stenosis even at a subclinical stage.
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Affiliation(s)
- Xinghua Wan
- The Department of Radiology, The People’s Hospital of Nanchang County, China
| | - Yu Xiao
- Medical College of Nanchang University, People’s Hospital of Jiangxi Province, China
| | - Zhenghua Liu
- Medical Imaging Center, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, China,Corresponding author at: No. 445, Bayi Road, Donghu District, Nanchang City 330006, China.
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25
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Peterson BS, Liu J, Dantec L, Newman C, Sawardekar S, Goh S, Bansal R. Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder. J Child Psychol Psychiatry 2022; 63:855-870. [PMID: 34762311 PMCID: PMC9091058 DOI: 10.1111/jcpp.13531] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/08/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management. METHODS We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively. RESULTS Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants. CONCLUSIONS Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.
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Affiliation(s)
- Bradley S. Peterson
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
| | - Jiaqi Liu
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | - Louis Dantec
- École Polytechnique Universitaire de Marseille, France
| | | | - Siddhant Sawardekar
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | | | - Ravi Bansal
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
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26
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Oberlin LE, Victoria LW, Ilieva I, Dunlop K, Hoptman MJ, Avari J, Alexopoulos GS, Gunning FM. Comparison of Functional and Structural Neural Network Features in Older Adults With Depression With vs Without Apathy and Association With Response to Escitalopram: Secondary Analysis of a Nonrandomized Clinical Trial. JAMA Netw Open 2022; 5:e2224142. [PMID: 35895056 PMCID: PMC9331093 DOI: 10.1001/jamanetworkopen.2022.24142] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
IMPORTANCE Apathy is prevalent among individuals with late-life depression and is associated with poor response to pharmacotherapy, including chronicity and disability. Elucidating brain networks associated with apathy and poor treatment outcomes can inform intervention development. OBJECTIVES To assess the brain network features of apathy among individuals with late-life depression and identify brain network abnormalities associated with poor antidepressant response. DESIGN, SETTING, AND PARTICIPANTS This secondary analysis of a single-group, open-label nonrandomized clinical trial of escitalopram conducted at an outpatient geriatric psychiatry clinic enrolled 40 adults aged 59 to 85 years with major depressive disorder from July 1, 2012, to July 31, 2019. INTERVENTIONS After a 2-week washout period, participants received escitalopram titrated to a target of 20 mg/d for 12 weeks. MAIN OUTCOMES AND MEASURES Baseline and posttreatment magnetic resonance imaging (MRI), clinical, and cognitive assessments were conducted. Functional MRI was used to map group differences in resting state functional connectivity (rsFC) of the salience network, and diffusion MRI connectometry was performed to evaluate pathway-level disruptions in structural connectivity. The Apathy Evaluation Scale was used to quantify apathy, and the Hamilton Depression Rating Scale (HAM-D) was used to quantify the primary outcome of depression severity. RESULTS Forty participants (26 women [65%]; mean [SD] age, 70.0 [6.6] years [range, 59-85 years]) with depression were included; 20 participants (50%) also had apathy. Relative to nonapathetic participants with depression, those with depression and apathy had lower rsFC of salience network seeds with the dorsolateral prefrontal cortex (DLPFC), premotor cortex, midcingulate cortex, and paracentral lobule and greater rsFC with the lateral temporal cortex and temporal pole (z score >2.7; Bonferroni-corrected threshold of P < .0125). Compared with participants without apathy, those with apathy had lower structural connectivity in the splenium, cingulum, and fronto-occipital fasciculus (t score >2.5; false discovery rate-corrected P = .02). Twenty-seven participants completed escitalopram treatment; 16 (59%) achieved remission (HAM-D score <10). Lower insula-DLPFC/midcingulate cortex rsFC was associated with less symptomatic improvement (HAM-D % change) (β [df] = 0.588 [26]; P = .001) and a higher likelihood of nonremission (odds ratio, 1.041 [95% CI, 1.003-1.081]; P = .04) after treatment and, in regression models, was a mediator of the association between baseline apathy and persistence of depression. Lower dorsal anterior cingulate-DLPFC/paracentral rsFC was associated with residual cognitive difficulties on measures of attention (β [df] = 0.445 [26]; P = .04) and executive function (β [df] = 0.384 [26]; P = .04). CONCLUSIONS AND RELEVANCE This study suggests that disturbances in connectivity between the salience network and other large-scale networks that support goal-directed behavior may give rise to apathy and may be associated with poor response of late-life depression to antidepressant pharmacotherapy. These network disturbances may serve as targets for novel interventions. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01728194.
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Affiliation(s)
- Lauren E. Oberlin
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
| | - Lindsay W. Victoria
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
| | - Irena Ilieva
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
| | - Katharine Dunlop
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
| | - Matthew J. Hoptman
- Clinical Research Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York
- Department of Psychiatry, NYU Grossman School of Medicine, New York, New York
| | - Jimmy Avari
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
| | - George S. Alexopoulos
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
| | - Faith M. Gunning
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
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27
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Luppi AI, Mediano PAM, Rosas FE, Holland N, Fryer TD, O'Brien JT, Rowe JB, Menon DK, Bor D, Stamatakis EA. A synergistic core for human brain evolution and cognition. Nat Neurosci 2022; 25:771-782. [PMID: 35618951 PMCID: PMC7614771 DOI: 10.1038/s41593-022-01070-0] [Citation(s) in RCA: 103] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 03/30/2022] [Indexed: 12/11/2022]
Abstract
How does the organization of neural information processing enable humans' sophisticated cognition? Here we decompose functional interactions between brain regions into synergistic and redundant components, revealing their distinct information-processing roles. Combining functional and structural neuroimaging with meta-analytic results, we demonstrate that redundant interactions are predominantly associated with structurally coupled, modular sensorimotor processing. Synergistic interactions instead support integrative processes and complex cognition across higher-order brain networks. The human brain leverages synergistic information to a greater extent than nonhuman primates, with high-synergy association cortices exhibiting the highest degree of evolutionary cortical expansion. Synaptic density mapping from positron emission tomography and convergent molecular and metabolic evidence demonstrate that synergistic interactions are supported by receptor diversity and human-accelerated genes underpinning synaptic function. This information-resolved approach provides analytic tools to disentangle information integration from coupling, enabling richer, more accurate interpretations of functional connectivity, and illuminating how the human neurocognitive architecture navigates the trade-off between robustness and integration.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK.
- The Alan Turing Institute, London, UK.
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
| | - Fernando E Rosas
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
- Data Science Institute, Imperial College London, London, UK
- Center for Complexity Science, Imperial College London, London, UK
| | - Negin Holland
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Tim D Fryer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Daniel Bor
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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28
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Luppi AI, Mediano PAM, Rosas FE, Allanson J, Pickard JD, Williams GB, Craig MM, Finoia P, Peattie ARD, Coppola P, Owen AM, Naci L, Menon DK, Bor D, Stamatakis EA. Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness. Commun Biol 2022; 5:384. [PMID: 35444252 PMCID: PMC9021270 DOI: 10.1038/s42003-022-03330-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 03/30/2022] [Indexed: 12/02/2022] Open
Abstract
The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK.
- The Alan Turing Institute, London, UK.
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
| | - Fernando E Rosas
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
- Data Science Institute, Imperial College London, London, UK
- Centre for Complexity Science, Imperial College London, London, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Paola Finoia
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Alexander R D Peattie
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Adrian M Owen
- The Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Daniel Bor
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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29
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Wang C, Ellingson BM, Salamon N, Holly LT. Recovery of Supraspinal Microstructural Integrity and Connectivity in Patients Undergoing Surgery for Degenerative Cervical Myelopathy. Neurosurgery 2022; 90:447-456. [PMID: 35076030 PMCID: PMC9514753 DOI: 10.1227/neu.0000000000001839] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 10/27/2021] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND It remains unknown if the progressive loss of axonal conduction along sensorimotor tracts can be recovered after surgery in patients with degenerative cervical myelopathy (DCM) and if subsequent adaptive microstructural changes are associated with the neurological improvement. OBJECTIVE To investigate the upstream recovery of microstructural integrity and reorganization of microstructural connectivity that occurs in patients with DCM after surgical decompression. METHODS Preoperative and postoperative cerebral diffusion tensor imaging and diffusion spectrum imaging data were collected for 22 patients with DCM (age = 56.9 ± 9.1 years). Paired t-tests were used to identify significant microstructural changes within cohorts, and correlation analysis was used to identify whether those changes are associated with neurological improvement. RESULTS Before surgery, higher structural connectivity (SC) was observed in the prefrontal/frontal lobes, anterior cingulate, the internal and external capsules, and the anterior, posterior, and superior regions of the corona radiata fibers. Following surgery, an increased modified Japanese Orthopaedic Association score was associated with increased SC from the primary sensorimotor regions to the posterior cingulate and precuneus; increased SC between the cerebellum and the bilateral lingual gyri; and decreased SC from areas of the limbic system to the basal ganglia and the frontal lobe. In addition, increased fractional anisotropy and normalized quantitative anisotropy values along white matter fibers responsible for conveying sensory information and motor coordination and planning were associated with neurological improvement of patients with DCM after surgery. CONCLUSION Recovery of microstructural integrity along the corticospinal tract and other sensorimotor pathways, together with supraspinal reorganization of microstructural connectivity within sensory and motor-related regions, was associated with neurological improvement after surgical decompression.
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Affiliation(s)
- Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA;
| | - Benjamin M. Ellingson
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA;
- Neuroscience Interdisciplinary Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA;
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA;
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA;
| | - Langston T. Holly
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA;
- Department of Orthopaedics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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Lee J, Ju G, Park H, Chung S, Son JW, Shin CJ, Lee SI, Kim S. Hippocampal Subfields and White Matter Connectivity in Patients with Subclinical Geriatric Depression. Brain Sci 2022; 12:brainsci12030329. [PMID: 35326285 PMCID: PMC8946804 DOI: 10.3390/brainsci12030329] [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: 01/16/2022] [Revised: 02/22/2022] [Accepted: 02/24/2022] [Indexed: 02/01/2023] Open
Abstract
Despite an abundance of research related to the functional and structural changes of the brain in patients with geriatric depression, knowledge related to early alterations such as decreased white matter connectivity and their association with cognitive decline remains lacking. We aimed to investigate early alterations in hippocampal microstructure and identify their associations with memory function in geriatric patients with subclinical depression. Nineteen participants with subclinical geriatric depression and 19 healthy controls aged ≥65 years exhibiting general cognitive function within the normal range were included in the study and underwent assessments of verbal memory. Hippocampal subfield volumes were determined based on T1-weighted magnetization-prepared rapid gradient echo (T1-MPRAGE) images, while group tractography and connectometry analyses were conducted using diffusion tensor images. Our findings indicated that the volumes of whole bilateral hippocampus, cornus ammonis (CA) 1, molecular layer, left subiculum, CA3, hippocampal tail, right CA4, and granule cell/molecular layers of the dentate gyrus (GC-ML-DG) were significantly smaller in the subclinical depression group than in the control group. In the subclinical depression group, verbal learning was positively correlated with the volumes of the CA1, GC-ML-DG, molecular layer, and whole hippocampus in the right hemisphere. The fractional anisotropy of the bilateral fornix was also significantly lower in the subclinical depression group and exhibited a positive correlation with verbal learning and recall in both groups. Our results suggest that hippocampal microstructure is disrupted and associated with memory in patients with subclinical depression.
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Affiliation(s)
- Jeonghwan Lee
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Gawon Ju
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Hyemi Park
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Seungwon Chung
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Jung-Woo Son
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Chul-Jin Shin
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Sang Ick Lee
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
| | - Siekyeong Kim
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea; (J.L.); (G.J.); (H.P.); (S.C.); (J.-W.S.); (C.-J.S.); (S.I.L.)
- Department of Psychiatry, College of Medicine, Chungbuk National University, Cheongju 28644, Korea
- Correspondence: ; Tel.: +82-43-269-6364; Fax: +82-43-267-7951
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Rahmani F, Wang Q, McKay NS, Keefe S, Hantler N, Hornbeck R, Wang Y, Hassenstab J, Schindler S, Xiong C, Morris JC, Benzinger TL, Raji CA. Sex-Specific Patterns of Body Mass Index Relationship with White Matter Connectivity. J Alzheimers Dis 2022; 86:1831-1848. [PMID: 35180116 PMCID: PMC9108572 DOI: 10.3233/jad-215329] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/31/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Obesity is an increasingly recognized modifiable risk factor for Alzheimer's disease (AD). Increased body mass index (BMI) is related to distinct changes in white matter (WM) fiber density and connectivity. OBJECTIVE We investigated whether sex differentially affects the relationship between BMI and WM structural connectivity. METHODS A cross-sectional sample of 231 cognitively normal participants were enrolled from the Knight Alzheimer Disease Research Center. Connectome analyses were done with diffusion data reconstructed using q-space diffeomorphic reconstruction to obtain the spin distribution function and tracts were selected using a deterministic fiber tracking algorithm. RESULTS We identified an inverse relationship between higher BMI and lower connectivity in the associational fibers of the temporal lobe in overweight and obese men. Normal to overweight women showed a significant positive association between BMI and connectivity in a wide array of WM fibers, an association that reversed in obese and morbidly obese women. Interaction analyses revealed that with increasing BMI, women showed higher WM connectivity in the bilateral frontoparietal and parahippocampal parts of the cingulum, while men showed lower connectivity in right sided corticostriatal and corticopontine tracts. Subgroup analyses demonstrated comparable results in participants with and without positron emission tomography or cerebrospinal fluid evidence of brain amyloidosis, indicating that the relationship between BMI and structural connectivity in men and women is independent of AD biomarker status. CONCLUSION BMI influences structural connectivity of WM differently in men and women across BMI categories and this relationship does not vary as a function of preclinical AD.
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Affiliation(s)
- Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Qing Wang
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Nicole S. McKay
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Sarah Keefe
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Nancy Hantler
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Russ Hornbeck
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Yong Wang
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Jason Hassenstab
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Suzanne Schindler
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Chengjie Xiong
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - John C. Morris
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Cyrus A. Raji
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
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Complete functional recovery in a child after endovascular treatment of basilar artery occlusion caused by spontaneous dissection: a case report. Childs Nerv Syst 2022; 38:1605-1612. [PMID: 34893933 PMCID: PMC9325841 DOI: 10.1007/s00381-021-05428-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 11/29/2021] [Indexed: 10/26/2022]
Abstract
Stroke caused by dissection of arteries of the vertebrobasilar system in children is still poorly investigated in terms of etiology, means of treatment, course of disease, and prognosis. The aim of this report was to describe the unusual course of a spontaneous dissection of the basilar artery (BA) in a child treated with endovascular techniques and to point out that the plasticity of the brain stem can fully compensate for structural damage caused by stroke. We report the case of a 15-year-old boy who suffered a wake-up stroke with BA occlusion caused by spontaneous dissection. A blood clot was aspirated from the false lumen and the true lumen re-opened, but the patient deteriorated a few hours later, and repeated angiography revealed that the intimal flap was detached, occluding the BA again. The lumen of BA was then reconstructed by a stent. Despite a large pons infarction, the patient was completely recovered 11 months after the onset. The case was analyzed with angiograms and magnetic resonance imaging, macroscopic and microscopic pathological analysis, computed tomographic angiography, magnetic resonance-based angiography, and diffusion tensor imaging. This case illustrates that applied endovascular techniques and intensive care measures can alter the course of potentially fatal brain stem infarction. Our multimodal analysis gives new insight into the anatomical basis for the plasticity mechanism of the brain stem.
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Brown JA, Jackson BS, Burton CR, Hoy JE, Sweeney JA, Pearlson GD, Keshavan MS, Keedy SS, Gershon ES, Tamminga CA, Clementz BA, McDowell JE. Reduced white matter microstructure in bipolar disorder with and without psychosis. Bipolar Disord 2021; 23:801-809. [PMID: 33550654 PMCID: PMC8514149 DOI: 10.1111/bdi.13055] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVES Affective and psychotic features overlap considerably in bipolar I disorder, complicating efforts to determine its etiology and develop targeted treatments. In order to clarify whether mechanisms are similar or divergent for bipolar disorder with psychosis (BDP) and bipolar disorder with no psychosis (BDNP), neurobiological profiles for both the groups must first be established. This study examines white matter structure in the BDP and BDNP groups, in an effort to identify portions of white matter that may differ between the bipolar and healthy groups or between the bipolar subgroups themselves. METHODS Diffusion-weighted imaging data were acquired from participants with BDP (n = 45), BDNP (n = 40), and healthy comparisons (HC) (n = 66). Fractional anisotropy (FA), radial diffusivity (RD), and spin distribution function (SDF) values indexing white matter diffusivity or spin density were calculated and compared between the groups. RESULTS In comparisons between both the bipolar groups and HC, FA (FDR < 0.00001) and RD (FDR = 0.0037) differed minimally, in localized portions of the left cingulum and corpus callosum, while reductions in SDF (FDR = 0.0002) were more widespread. The bipolar subgroups did not differ from each other on FA, RD, or SDF metrics. CONCLUSIONS Together, these results demonstrate a novel profile of white matter differences in bipolar disorder and suggest that this white matter pathology is associated with the affective disturbance common to those with bipolar disorder rather than the psychotic features unique to some. The white matter alterations identified in this study may provide substrates for future studies examining specific mechanisms that target affective domains of illness.
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Affiliation(s)
- Jennifer A Brown
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Brooke S Jackson
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Courtney R Burton
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Jennifer E Hoy
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Godfrey D Pearlson
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.,Institute of Living/Hartford Hospital, Hartford, CT, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Hospital, Harvard Medical School, Boston, MA, USA
| | - Sarah S Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, USA
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
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Language Tasks and the Network Control Role of the Left Inferior Frontal Gyrus. eNeuro 2021; 8:ENEURO.0382-20.2021. [PMID: 34244340 PMCID: PMC8431826 DOI: 10.1523/eneuro.0382-20.2021] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 04/30/2021] [Accepted: 05/03/2021] [Indexed: 11/21/2022] Open
Abstract
Recent work has combined cognitive neuroscience and control theory to make predictions about cognitive control functions. Here, we test a link between whole-brain theories of semantics and the role of the left inferior frontal gyrus (LIFG) in controlled language performance using network control theory (NCT), a branch of systems engineering. Specifically, we examined whether two properties of node controllability, boundary and modal controllability, were linked to semantic selection and retrieval on sentence completion and verb generation tasks. We tested whether the controllability of the left IFG moderated language selection and retrieval costs and the effects of continuous θ burst stimulation (cTBS), an inhibitory form of transcranial magnetic stimulation (TMS) on behavior in 41 human subjects (25 active, 16 sham). We predicted that boundary controllability, a measure of the theoretical ability of a node to integrate and segregate brain networks, would be linked to word selection in the contextually-rich sentence completion task. In contrast, we expected that modal controllability, a measure of the theoretical ability of a node to drive the brain into specifically hard-to-reach states, would be linked to retrieval on the low-context verb generation task. Boundary controllability was linked to selection and to the ability of TMS to reduce response latencies on the sentence completion task. In contrast, modal controllability was not linked to performance on the tasks or TMS effects. Overall, our results suggest a link between the network integrating role of the LIFG and selection and the overall semantic demands of sentence completion.
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Tsai CJ, Lin HY, Tseng IWY, Gau SSF. White matter microstructural integrity correlates of emotion dysregulation in children with ADHD: A diffusion imaging tractography study. Prog Neuropsychopharmacol Biol Psychiatry 2021; 110:110325. [PMID: 33857524 DOI: 10.1016/j.pnpbp.2021.110325] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 04/06/2021] [Accepted: 04/09/2021] [Indexed: 01/25/2023]
Abstract
BACKGROUND Emotion dysregulation (ED) is prevalent in youths with attention-deficit hyperactivity disorder (ADHD) and causes more social impairment and poor adaptive function. Alterations in the integrity of white matter (WM) tracts might have important implications for affective processing related to ED. However, little is known about the WM correlates underpinning ED in ADHD. METHODS Using diffusion spectrum image tractography, we obtained generalized fractional anisotropy (GFA) values of 76 WM tracts in 77 children with ADHD and 105 typically developing controls (TDC). ED severity was defined by the dysregulation profile from the child behavior checklist. Canonical correlation analysis (CCA) was performed to identify modes that relate WM microstructural property to ED severity and cognitive measures. RESULTS The application of CCA identified one significant mode (r = 0.638, FWE-corrected p = 0.046) of interdependencies between WM property patterns and diagnosis, ADHD total symptom levels, dysregulation by diagnosis interaction, and full-scale intellectual quotient (FIQ). GFA values of 19 WM tracts that were linked to affective-processing, sensory-processing and integration, and cognitive control circuitry were positively correlated with ED severity in TDC but negatively correlated with ED severity in ADHD. ADHD symptom severity and diagnosis were negatively associated with the GFA patterns of this set of tract bundles. In contrast, FIQ was positively correlated with this set of tract bundles. CONCLUSIONS This study used the CCA to show that children with ADHD and TDC had distinct multivariate associations between ED severity (diagnosis by ED interaction) and microstructural property in a set of WM tracts. These tracts interconnect the cortical regions that are principally involved in emotion processing, integration, and cognitive control in multiple brain systems. The WM microstructure integrity impairment might be an essential correlate of emotion dysregulation in ADHD.
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Affiliation(s)
- Chia-Jui Tsai
- Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre and Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Isaac Wen-Yih Tseng
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan.
| | - Susan Shur-Fen Gau
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences and Department of Psychology, National Taiwan University, Taipei, Taiwan.
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Adil SM, Calabrese E, Charalambous LT, Cook JJ, Rahimpour S, Atik AF, Cofer GP, Parente BA, Johnson GA, Lad SP, White LE. A high-resolution interactive atlas of the human brainstem using magnetic resonance imaging. Neuroimage 2021; 237:118135. [PMID: 33951517 PMCID: PMC8480283 DOI: 10.1016/j.neuroimage.2021.118135] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/15/2021] [Accepted: 04/28/2021] [Indexed: 12/30/2022] Open
Abstract
Conventional atlases of the human brainstem are limited by the inflexible, sparsely-sampled, two-dimensional nature of histology, or the low spatial resolution of conventional magnetic resonance imaging (MRI). Postmortem high-resolution MRI circumvents the challenges associated with both modalities. A single human brainstem specimen extending from the rostral diencephalon through the caudal medulla was prepared for imaging after the brain was removed from a 65-year-old male within 24 h of death. The specimen was formalin-fixed for two weeks, then rehydrated and placed in a custom-made MRI compatible tube and immersed in liquid fluorocarbon. MRI was performed in a 7-Tesla scanner with 120 unique diffusion directions. Acquisition time for anatomic and diffusion images were 14 h and 208 h, respectively. Segmentation was performed manually. Deterministic fiber tractography was done using strategically chosen regions of interest and avoidance, with manual editing using expert knowledge of human neuroanatomy. Anatomic and diffusion images were rendered with isotropic resolutions of 50 μm and 200 μm, respectively. Ninety different structures were segmented and labeled, and 11 different fiber bundles were rendered with tractography. The complete atlas is available online for interactive use at https://www.civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2F. This atlas presents multiple contrasting datasets and selected tract reconstruction with unprecedented resolution for MR imaging of the human brainstem. There are immediate applications in neuroanatomical education, with the potential to serve future applications for neuroanatomical research and enhanced neurosurgical planning through "safe" zones of entry into the human brainstem.
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Affiliation(s)
- Syed M Adil
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States; Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Evan Calabrese
- University of California San Francisco, Department of Radiology & Biomedical Imaging, San Francisco, CA, United States.
| | - Lefko T Charalambous
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States; Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - James J Cook
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States.
| | - Ahmet F Atik
- Department of Neurosurgery, Cleveland Clinic, Cleveland, OH, United States.
| | - Gary P Cofer
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Beth A Parente
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States.
| | - G Allan Johnson
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Shivanand P Lad
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States.
| | - Leonard E White
- Department of Neurology, Duke University Medical Center, Durham, NC, United States; Duke Institute for Brain Sciences, Duke University, Durham NC, United States.
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Mehrabinejad MM, Rafei P, Sanjari Moghaddam H, Sinaeifar Z, Aarabi MH. Sex Differences are Reflected in Microstructural White Matter Alterations of Musical Sophistication: A Diffusion MRI Study. Front Neurosci 2021; 15:622053. [PMID: 34366766 PMCID: PMC8339302 DOI: 10.3389/fnins.2021.622053] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 06/28/2021] [Indexed: 11/23/2022] Open
Abstract
Background: The human-specified ability to engage with different kinds of music in sophisticated ways is named “Musical Sophistication.” Herein, we investigated specific white matter (WM) tracts that are associated with musical sophistication and musicality in both genders, separately, using Diffusion MRI connectometry approach. We specifically aimed to explore potential sex differences regarding WM alterations correlated with musical sophistication. Methods: 123 healthy participants [70 (56.9%) were male, mean age = 36.80 ± 18.86 year], who were evaluated for musical sophistication using Goldsmiths Musical Sophistication Index (Gold-MSI) self-assessment instrument from the LEMON database, were recruited in this study. The WM correlates of two Gold-MSI subscales (active engagement and music training) were analyzed. Images were prepared and analyzed with diffusion connectometry to construct the local connectome. Multiple regression models were then fitted to address the correlation of local connectomes with Gold-MSI components with the covariates of age and handedness. Results: a significant positive correlation between WM integrity in the corpus callosum (CC), right corticospinal tract (CST), cingulum, middle cerebellar peduncle (MCP), bilateral parieto-pontine tract, bilateral cerebellum, and left arcuate fasciculus (AF) and both active engagement [false discovery rate (FDR) = 0.008] and music training (FDR = 0.057) was detected in males. However, WM integrity in the body of CC, MCP, and cerebellum in females showed an inverse association with active engagement (FDR = 0.046) and music training (FDR = 0.032). Conclusion: WM microstructures with functional connection with motor and somatosensory areas (CST, cortico-pontine tracts, CC, cerebellum, cingulum, and MCP) and language processing area (AF) have significant correlation with music engagement and training. Our findings show that these associations are different between males and females, which could potentially account for distinctive mechanisms related to musical perception and musical abilities across genders.
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Affiliation(s)
| | - Parnian Rafei
- Department of Psychology, Faculty of Psychology and Education, University of Tehran, Tehran, Iran
| | | | - Zeinab Sinaeifar
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Hadi Aarabi
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Department of Neuroscience, Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
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Li Z, Dolui S, Habes M, Bassett DS, Wolk D, Detre JA. Predicted disconnectome associated with progressive periventricular white matter ischemia. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2021; 2:100022. [PMID: 36324715 PMCID: PMC9616229 DOI: 10.1016/j.cccb.2021.100022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 11/21/2022]
Abstract
We used a virtual lesion DTI fiber tracking approach with healthy subject DTI data and simulated periventricular white matter (PVWM) lesion masks to predict the sequence of connectivity changes associated with progressive PVWM ischemia. We found that the optic radiations, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, corpus callosum, temporopontine tract and fornix were affected in early simulated ischemic injury, and that the connectivity of subcortical, cerebellar, and visual regions were significantly disrupted with increasing simulated lesion severity. The results of this study provide insights into the spatial-temporal changes of the brain structural connectome under progressive PVWM ischemia. The virtual lesion approach provides a meaningful proxy to the spatial-temporal changes of the brain's structural connectome and can be used to further characterize the cognitive sequelae of progressive PVWM ischemia in both normal aging and dementia.
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Affiliation(s)
- Zhengjun Li
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
| | - Sudipto Dolui
- Radiology, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
| | - Mohamad Habes
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Radiology, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
- Biggs institute neuroimaging core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, USA
| | - Danielle S. Bassett
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Psychiatry, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
- The Santa Fe Institute, USA
| | - David Wolk
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
| | - John A. Detre
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Radiology, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
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Posterior Precuneus is Highly Connected to Medial Temporal Lobe Revealed by Tractography and White Matter Dissection. Neuroscience 2021; 466:173-185. [PMID: 34015372 DOI: 10.1016/j.neuroscience.2021.05.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 03/16/2021] [Accepted: 05/08/2021] [Indexed: 01/19/2023]
Abstract
The precuneus, involved in various cognitive processes, is considered to form the midline core of the default mode network (DMN), while the medial temporal lobe (MTL) is a subsystem of the DMN. Until now, the anatomical study of the precuneus-MTL connection is limited in humans. One possible reason is the precuneus' territory of the posteromedial cortex (PMC) is inconsistent across studies. The primary purpose of this study is to investigate the structural connectivity (SC) of precuneus-MTL, focusing on its anatomical organization using the Human Connectome Project Multi-modal Parcellation (HCP MMP) atlas. We first conducted the quantitative tractography analyses using the HCP dataset. The major streamlines originated from the posterior precuneus and were projected to the MTL extensively. Next, to complement the tractography data, we conducted the white matter dissection in the post-mortem human brain. We observed the major fiber bundles arise from the posterior precuneus extending to the anterior parahippocampal gyrus, which could support our tractography results. Then we analyzed the relationship between SC and resting-state functional connectivity (rsFC) of the precuneus-MTL. Although the SC-rsFC correlation was scarce on the whole, the posterior precuneus (POS2, 7Pm, 7m) showed a relatively high correlation (r = 0.38349, p < 0.05) with the posterior MTL (PreS, H, ProS, PHA1, PHA2). Our findings suggest the posterior precuneus is highly connected to MTL structurally, which could have an effect on the resting-state functional connectivity. In addition, the precuneus might consist of the heterogeneous connectivity-based subdivisions.
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Luppi AI, Craig MM, Coppola P, Peattie ARD, Finoia P, Williams GB, Allanson J, Pickard JD, Menon DK, Stamatakis EA. Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury. Neuroimage Clin 2021; 30:102682. [PMID: 34215152 PMCID: PMC8102619 DOI: 10.1016/j.nicl.2021.102682] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 03/30/2021] [Accepted: 04/18/2021] [Indexed: 12/24/2022]
Abstract
Self-similarity is ubiquitous throughout natural phenomena, including the human brain. Recent evidence indicates that fractal dimension of functional brain networks, a measure of self-similarity, is diminished in patients diagnosed with disorders of consciousness arising from severe brain injury. Here, we set out to investigate whether loss of self-similarity is observed in the structural connectome of patients with disorders of consciousness. Using diffusion MRI tractography from N = 11 patients in a minimally conscious state (MCS), N = 10 patients diagnosed with unresponsive wakefulness syndrome (UWS), and N = 20 healthy controls, we show that fractal dimension of structural brain networks is diminished in DOC patients. Remarkably, we also show that fractal dimension of structural brain networks is preserved in patients who exhibit evidence of covert consciousness by performing mental imagery tasks during functional MRI scanning. These results demonstrate that differences in fractal dimension of structural brain networks are quantitatively associated with chronic loss of consciousness induced by severe brain injury, highlighting the close connection between structural organisation of the human brain and its ability to support cognitive function.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom.
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom
| | - Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom
| | - Alexander R D Peattie
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom
| | - Guy B Williams
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), Cambridge CB2 0QQ, United Kingdom
| | - Judith Allanson
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom
| | - John D Pickard
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), Cambridge CB2 0QQ, United Kingdom
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), Cambridge CB2 0QQ, United Kingdom
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, United Kingdom
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41
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Gleichgerrcht E, Greenblatt AS, Kellermann TS, Rowland N, Vandergrift WA, Edwards J, Davis KA, Bonilha L. Patterns of seizure spread in temporal lobe epilepsy are associated with distinct white matter tracts. Epilepsy Res 2021; 171:106571. [PMID: 33582534 PMCID: PMC7981262 DOI: 10.1016/j.eplepsyres.2021.106571] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 01/31/2021] [Accepted: 02/03/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE It is commonly hypothesized that seizure spread patterns in patients with focal epilepsy are associated with structural brain pathways. However, this relationship is poorly understood and has not been fully demonstrated in patients with temporal lobe epilepsy. Here, we sought to determine whether directionality of seizure spread (DSS) is associated with specific cerebral white matter tracts in patients with temporal lobe epilepsy. METHODS Thirty-three adult patients with temporal lobe epilepsy who underwent stereoelectroencephalography (sEEG) and magnetic resonance diffusion tensor imaging (MR-DTI) as part of their standard-of-care clinical evaluation were included in the study. DSS was defined as anterior-posterior (AP) or medial-lateral (ML) spread based upon sEEG evaluation by two independent specialists who demonstrated excellent inter-rater agreement (Cohen's kappa = .92). DTI connectometry was used to assess differences between seizure spread pattern groups along major fiber pathways regarding fractional anisotropy (FA). RESULTS Twenty-four participants showed seizures with AP spread and nine participants showed seizures with ML spread. There were no significant differences between the groups on their demographic and clinical profile. Patients with ML seizures had higher FA along the corpus callosum and, to a lesser degree, some portions of the bilateral cingulate tracts. In contrast, patients with AP seizures had higher FA along several anterior-posterior white matter projections bundles, including the cingulate fasciculus and the inferior longitudinal, with significantly less involvement of the corpus callosum compared with ML seizures. SIGNIFICANCE This study confirms the hypothesis that the anatomical pattern of electrophysiological ictal propagation is associated with the structural reinforcement of supporting pathways in temporal lobe epilepsy. This observation can help elucidate mechanisms of ictal propagation and may guide future translational approaches to curtail seizure spread.
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Affiliation(s)
| | - Adam S Greenblatt
- Medical University of South Carolina, Charleston, SC, USA; University of Pennsylvania, Philadelphia, PA, USA
| | | | - Nathan Rowland
- Medical University of South Carolina, Charleston, SC, USA
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Buldyrev SV, Meng X, Reese TG, Mortazavi F, Rosene DL, Stanley HE, Wedeen VJ. Diffusion interactions between crossing fibers of the brain. Magn Reson Med 2021; 86:429-441. [PMID: 33619754 DOI: 10.1002/mrm.28702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 11/11/2022]
Abstract
PURPOSE Recent observations of several preferred orientations of diffusion in deep white matter may indicate either (a) that axons in different directions are independently bundled in thick sheets and function noninteractively, or more interestingly, (b) that the axons are closely interwoven and would exhibit branching and sharp turns. This study aims to investigate whether the dependence of dMRI Q-ball signal on the interpulse time Δ can decode the smaller-than-voxel-size brain structure, in particular, to distinguish scenarios (a) and (b). METHODS High-resolution Q-ball images of a healthy brain taken with b = 8000 s/mm2 for 3 different values of Δ were analyzed. The exchange of water molecules between crossing fibers was characterized by the fourth Fourier coefficient f 4 ( Δ ) of the signal profile in the plane of crossing. To interpret the empirical results, a model consisting of differently oriented parallel sheets of cylinders was developed. Diffusion of water molecules inside and outside cylinders was simulated by the Monte Carlo method. RESULTS Simulations predict that f 4 ( Δ ) , agreeing with the empirical results, must increase with Δ for large b-values, but may peak at a typical Δ that depends on the thickness of the cylinder sheets for intermediate b-values. Thus, the thickness of axon layers in voxels with 2 predominant orientations can be detected from empirical f 4 ( Δ ) taken at smaller b-values. CONCLUSION Based on the simulation results, recommendations are made on how to design a dMRI experiment with optimal b-value and range of Δ in order to measure the thickness of axon sheets in the white matter, hence to distinguish (a) and (b).
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Affiliation(s)
| | - Xiangyi Meng
- Center for Polymer Studies, Department of Physics, Boston University, Boston, MA, USA.,Center for Complex Network Research, Department of Physics, Northeastern University, Boston, MA, USA
| | - Timothy G Reese
- Department of Radiology, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Farzad Mortazavi
- Department of Anatomy and Neurobiology, Boston University, Boston, MA, USA
| | - Douglas L Rosene
- Department of Anatomy and Neurobiology, Boston University, Boston, MA, USA
| | - H Eugene Stanley
- Center for Polymer Studies, Department of Physics, Boston University, Boston, MA, USA
| | - Van J Wedeen
- Department of Radiology, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
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Ibrahim I, Škoch A, Herynek V, Jírů F, Tintěra J. Magnetic resonance tractography of the lumbosacral plexus: Step-by-step. Medicine (Baltimore) 2021; 100:e24646. [PMID: 33578590 PMCID: PMC10545402 DOI: 10.1097/md.0000000000024646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 12/22/2020] [Accepted: 01/13/2021] [Indexed: 11/25/2022] Open
Abstract
ABSTRACT MR tractography of the lumbosacral plexus (LSP) is challenging due to the difficulty of acquiring high quality data and accurately estimating the neuronal tracts. We proposed an algorithm for an accurate visualization and assessment of the major LSP bundles using the segmentation of the cauda equina as seed points for the initial starting area for the fiber tracking algorithm.Twenty-six healthy volunteers underwent MRI examinations on a 3T MR scanner using the phased array coils with optimized measurement protocols for diffusion-weighted images and coronal T2 weighted 3D short-term inversion recovery sampling perfection with application optimized contrast using varying flip angle evaluation sequences used for LSP fiber reconstruction and MR neurography (MRN).The fiber bundles reconstruction was optimized in terms of eliminating the muscle fibers contamination using the segmentation of cauda equina, the effects of the normalized quantitative anisotropy (NQA) and angular threshold on reconstruction of the LSP. In this study, the NQA parameter has been used for fiber tracking instead of fractional anisotropy (FA) and the regions of interest positioning was precisely adjusted bilaterally and symmetrically in each individual subject.The diffusion data were processed in individual L3-S2 nerve fibers using the generalized Q-sampling imaging algorithm. Data (mean FA, mean diffusivity, axial diffusivity and radial diffusivity, and normalized quantitative anisotropy) were statistically analyzed using the linear mixed-effects model. The MR neurography was performed in MedINRIA and post-processed using the maximum intensity projection method to demonstrate LSP tracts in multiple planes.FA values significantly decreased towards the sacral region (P < .001); by contrast, mean diffusivity, axial diffusivity, radial diffusivity and NQA values significantly increased towards the sacral region (P < .001).Fiber tractography of the LSP was feasible in all examined subjects and closely corresponded with the nerves visible in the maximum intensity projection images of MR neurography. Usage of NQA instead of FA in the proposed algorithm enabled better separation of muscle and nerve fibers.The presented algorithm yields a high quality reconstruction of the LSP bundles that may be helpful both in research and clinical practice.
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Affiliation(s)
- Ibrahim Ibrahim
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, MR Unit
| | - Antonín Škoch
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, MR Unit
| | - Vít Herynek
- Center for Advanced Preclinical Imaging, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Filip Jírů
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, MR Unit
| | - Jaroslav Tintěra
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, MR Unit
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Ghulam-Jelani Z, Barrios-Martinez J, Eguiluz-Melendez A, Gomez R, Anania Y, Yeh FC. Redundancy circuits of the commissural pathways in human and rhesus macaque brains. Hum Brain Mapp 2021; 42:2250-2261. [PMID: 33559959 PMCID: PMC8046059 DOI: 10.1002/hbm.25363] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/06/2021] [Accepted: 01/21/2021] [Indexed: 12/25/2022] Open
Abstract
It has been hypothesized that the human brain has less redundancy than animals, but the structural evidence has not been identified to confirm this claim. Here, we report three redundancy circuits of the commissural pathways in primate brains, namely the orbitofrontal, temporal, and occipital redundancy circuits of the anterior commissure and corpus callosum. Each redundancy circuit has two distinctly separated routes connecting a common pair of cortical regions. We mapped their trajectories in human and rhesus macaque brains using individual and population‐averaged tractography. The dissection results confirmed the existence of these redundancy circuits connecting the orbitofrontal lobe, amygdala, and visual cortex. The volume analysis showed a significant reduction in the orbitofrontal and occipital redundancy circuits of the human brain, whereas the temporal redundancy circuit had a substantial organizational difference between the human and rhesus macaque. Our results support the hypothesis that the human brain has less redundancy in the commissural pathways than that of the rhesus macaque brain. Further studies are needed to explore its neuropathological implications.
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Affiliation(s)
- Zulfar Ghulam-Jelani
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Jessica Barrios-Martinez
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Aldo Eguiluz-Melendez
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Ricardo Gomez
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Yury Anania
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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Detection of cerebral reorganization associated with degenerative cervical myelopathy using diffusion spectral imaging (DSI). J Clin Neurosci 2021; 86:164-173. [PMID: 33775321 DOI: 10.1016/j.jocn.2021.01.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 11/09/2020] [Accepted: 01/07/2021] [Indexed: 11/23/2022]
Abstract
Degenerative Cervical Myelopathy (DCM) is a spinal cord disorder that causes significant physical disabilities in older patients. While most DCM research focuses on the spinal cord, widespread reorganization of the brain may occur to compensate for functional impairment. This observational study used diffusion spectrum imaging (DSI) to examine reorganization of cerebral white matter associated with neurological impairment as measured by the modified Japanese Orthopedic Association (mJOA), and severity of neck disability as measured by the Neck Disability Index (NDI) score. A total of 47 patients were included in the cervical spondylosis (CS) cohort: 38 patients with DCM (mean mJOA = 14.6, and mean NDI = 12.0), and 9 neurologically asymptomatic patients with spinal cord compression (mJOA = 18, and mean NDI = 7.0). 28 healthy volunteers (HCs) served as the control group. Lower generalized fractional anisotropy (GFA) was observed throughout much of the brain in patients compared to HCs (p < 0.05). Fiber pathways associated with somatosensory functions, such as the corpus callosum and corona radiata, showed increased quantitative anisotropy (QA) in patients compared to HCs. Correlation analyses further suggested that structural connectivity was enhanced to compensate for neurological dysfunction within sensorimotor regions, where fibers such as the posterior corona radiata had NQA values that were negatively associated with mJOA (p = 0.0020, R2 = 0.2935) and positively associated with NDI score (p = 0.0164, R2 = 0.1889). Altogether, these results suggest that DCM and neurologically asymptomatic spinal cord compression patients tend to have long-term reorganization within the brain, particularly in those regions responsible for the perception and integration of sensory information, motor regulation, and pain modulation.
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Wang YH, Wang ZM, Wei PH, Lu C, Fan XT, Ren LK, Shan YZ, Lu J, Zhao GG. Lateralizing the affected side of hippocampal sclerosis with quantitative high angular resolution diffusion scalars: a preliminary approach validated by diffusion spectrum imaging. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:297. [PMID: 33708924 PMCID: PMC7944293 DOI: 10.21037/atm-20-5719] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Conflicts in regarding the lateralization of the seizure onset for mesial temporal lobe epilepsy (MTLE) are frequently encountered during presurgical evaluation. As a more elaborate, quantified protocol, indices of diffusion spectrum imaging (DSI) might be sensitive to evaluate the seizure involvement. However, the accuracy was less revealed. Herein, we determined the lateralizing value of the DSI indices among MTLE patients. Methods Eleven MTLE patients were enrolled together with 11 matched health contrasts. All the participants underwent a DSI scan and with reconstruction of the diffusion scalar, including quantitative anisotropy (QA), isotropic (ISO), and track density imaging (TDI) values. Statistics of these indices were applied to identify the differences between the healthy and ipsilateral sides, and those between the patients and the controls, with special attention to areas of the crura of fornix (FORX), the parahippocampal radiation of the cingulum (PHCR), the hippocampus (HP), parahippocampus (PHC), amygdala (AM) and entorhinal cortex (EC). Results Regarding lateralization, TDI of the FORX and the PHCR reached an AUC value of 0.95 and 0.93, respectively (P<0.05), and QA, ISO, TDI of the PHCR, as well as TDI of the FORX were statistically significant amongst the laterals of the patients (P<0.05). Also, the QA of the PHCR were statistically different in the patients' ipsilateral side relative to the contrasts (P<0.017). The diffusion level on different grey matter structures were significantly decreased including HP, AM and EC in GQI space (P<0.017). Conclusions The quantitative diffusion scalars of the DSI, especially TDI of the FORX and the PHCR, are sensitive indices to define the ipsilateral side for MTLE patients. For preliminary exploration, the use of quantitative DSI scalars may help to improve the seizure outcome by increasing the accuracy of localization and lateralization for MTLE.
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Affiliation(s)
- Yi-He Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhen-Ming Wang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Peng-Hu Wei
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Chao Lu
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiao-Tong Fan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lian-Kun Ren
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yong-Zhi Shan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Guo-Guang Zhao
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorder, Beijing, China
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Luppi AI, Stamatakis EA. Combining network topology and information theory to construct representative brain networks. Netw Neurosci 2021; 5:96-124. [PMID: 33688608 PMCID: PMC7935031 DOI: 10.1162/netn_a_00170] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 09/23/2020] [Indexed: 01/21/2023] Open
Abstract
Network neuroscience employs graph theory to investigate the human brain as a complex network, and derive generalizable insights about the brain's network properties. However, graph-theoretical results obtained from network construction pipelines that produce idiosyncratic networks may not generalize when alternative pipelines are employed. This issue is especially pressing because a wide variety of network construction pipelines have been employed in the human network neuroscience literature, making comparisons between studies problematic. Here, we investigate how to produce networks that are maximally representative of the broader set of brain networks obtained from the same neuroimaging data. We do so by minimizing an information-theoretic measure of divergence between network topologies, known as the portrait divergence. Based on functional and diffusion MRI data from the Human Connectome Project, we consider anatomical, functional, and multimodal parcellations at three different scales, and 48 distinct ways of defining network edges. We show that the highest representativeness can be obtained by using parcellations in the order of 200 regions and filtering functional networks based on efficiency-cost optimization-though suitable alternatives are also highlighted. Overall, we identify specific node definition and thresholding procedures that neuroscientists can follow in order to derive representative networks from their human neuroimaging data.
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Affiliation(s)
- Andrea I Luppi
- Division of Anesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Emmanuel A Stamatakis
- Division of Anesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
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Ye Z, Gary SE, Sun P, Mustafi SM, Glenn GR, Yeh FC, Merisaari H, Song C, Yang R, Huang GS, Kao HW, Lin CY, Wu YC, Jensen JH, Song SK. The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi-tensor model vs. diffusion orientation distribution function. NMR IN BIOMEDICINE 2021; 34:e4414. [PMID: 33015890 PMCID: PMC9743958 DOI: 10.1002/nbm.4414] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 08/23/2020] [Accepted: 09/06/2020] [Indexed: 05/30/2023]
Abstract
Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when compared with the gold standard (r2 = 0.92, P = 1.9 × 10-9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.
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Affiliation(s)
- Zezhong Ye
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Sam E. Gary
- Medical Scientist Training Program, University of Alabama at Birmingham, Birmingham, AL 35294
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Sourajit Mitra Mustafi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202
| | - George Russell Glenn
- Department of Radiology and Imaging Science, Emory University School of Medicine, Atlanta, GA 30322
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213
| | - Harri Merisaari
- Department of Diagnostic Radiology, University of Turku, Turku, Finland 20014
| | - Chunyu Song
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130
| | - Ruimeng Yang
- Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China
| | - Guo-Shu Huang
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan 114
| | - Hung-Wen Kao
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan 114
| | | | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202
| | - Jens H. Jensen
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC 29425
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC 29425
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
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Rahmani F, Sanjari Moghaddam H, Aarabi MH. Intact microstructure of the right corticostriatal pathway predicts creative ability in healthy adults. Brain Behav 2020; 10:e01895. [PMID: 33063472 PMCID: PMC7749564 DOI: 10.1002/brb3.1895] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 09/19/2020] [Accepted: 09/26/2020] [Indexed: 12/26/2022] Open
Abstract
INTRODUCTION Creativity is one of the most complex functions of the human brain. The corticostriatal pathways have been implicated in creative thinking, yet few studies have addressed the microstructural underpinnings of creative ability, especially those related to the corticostriatal dopaminergic circuitry. We hypothesized that performance in creativity tests can be predicted based on diffusion metrics of the corticostriatal pathways and basal ganglia. METHODS A total of 37 healthy adults were included. Neuropsychological tests of creativity, including the alternative uses task (AUT), test of creative imagery abilities (TCIA), remote associates test (RAT), and creative achievement questionnaire (CAQ), as well as diffusion MRI data were acquired for each participant. RESULTS We demonstrated an independent effect of TCIA originality and TCIA transformativeness subscores, and RAT score in predicting the mean diffusivity (MD), mean axial diffusivity (AD), mean fractional anisotropy (FA), and mean generalized FA of the right corticostriatal pathway. We also observed independent effects of AUT elaboration subscore in predicting the AD of the right substantia nigra, and radial diffusivity (RD) of the right globus pallidus. CONCLUSION Our results put a further spin on the "creative right brain" notion and question the presence of high-creative and low-creative networks in the brain.
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Affiliation(s)
- Farzaneh Rahmani
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA.,NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
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Torrecillas-Martínez L, Catena A, O'Valle F, Solano-Galvis C, Padial-Molina M, Galindo-Moreno P. On the Relationship Between White Matter Structure and Subjective Pain. Lessons From an Acute Surgical Pain Model. Front Hum Neurosci 2020; 14:558703. [PMID: 33328926 PMCID: PMC7732636 DOI: 10.3389/fnhum.2020.558703] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Accepted: 10/26/2020] [Indexed: 11/21/2022] Open
Abstract
Background: Pain has been associated with structural changes of the brain. However, evidence regarding white matter changes in response to acute pain protocols is still scarce. In the present study, we assess the existence of differences in brain white matter related to pain intensity reported by patients undergoing surgical removal of a mandibular impacted third molar using diffusion tensor imaging (DTI) analysis. Methods: 30 participants reported their subjective pain using a visual analog scale at three postsurgical stages: under anesthesia, in pain, and after the administration of an analgesic. The diffusion data were acquired prior to surgery. Results: DTI analysis yielded significant positive associations of fractional anisotropy in white matter areas related to pain processing (corticospinal tract, corona radiata, corpus callosum) with the differences in pain between the three postsurgery stages. Extent and location of these associations depended on the magnitude of the subjective pain differences. Tractography analysis indicated that some pain–tract associations are significant only when pain stage is involved in the contrast (posterior corona radiata), while others (middle cerebellar peduncle, pontine crossing) are only when anesthesia is involved in the contrast. Conclusions: The association of white matter fractional anisotropy and connectivity, measured before the pain stages, with subjective pain depends on the magnitude of the differences in pain scores.
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Affiliation(s)
- Laura Torrecillas-Martínez
- Department of Oral Surgery and Implant Dentistry, School of Dentistry, University of Granada, Granada, Spain
| | - Andrés Catena
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain
| | - Francisco O'Valle
- Department of Pathology, School of Medicine and Instituto de Biopatología y Medicina Reparativa, University of Granada, Granada, Spain
| | - César Solano-Galvis
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain
| | - Miguel Padial-Molina
- Department of Oral Surgery and Implant Dentistry, School of Dentistry, University of Granada, Granada, Spain
| | - Pablo Galindo-Moreno
- Department of Oral Surgery and Implant Dentistry, School of Dentistry, University of Granada, Granada, Spain
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