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Wu J, Yang J, Yuan Z, Zhang J, Zhang Z, Qin T, Li X, Deng H, Gong L. Functional connectome gradient predicts clinical symptoms of chronic insomnia disorder. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111120. [PMID: 39154930 DOI: 10.1016/j.pnpbp.2024.111120] [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: 05/29/2024] [Revised: 07/30/2024] [Accepted: 08/15/2024] [Indexed: 08/20/2024]
Abstract
Insomnia is the second most prevalent psychiatric disorder worldwide, but the understanding of the pathophysiology of insomnia remains fragmented. In this study, we calculated the connectome gradient in 50 chronic insomnia disorder (CID) patients and 38 healthy controls (HC) to assess changes due to insomnia and utilized these gradients in a connectome-based predictive modeling (CPM) to predict clinical symptoms associated with insomnia. The results suggested that insomnia led to significant alterations in the functional gradients of some brain areas. Specifically, the gradient scores in the middle frontal gyrus, superior anterior cingulate gyrus, and right nucleus accumbens were significantly higher in the CID patients than in the HC group, whereas the scores in the middle occipital gyrus, right fusiform gyrus, and right postcentral gyrus were significantly lower than in the HC group. Further correlation analysis revealed that the right middle frontal gyrus is positively correlated with the self-rating anxiety scale (r=0.3702). Additionally, the prediction model built with functional gradients could well predict the sleep quality (r=0.5858), anxiety (r=0.6150), and depression (r=0.4022) levels of insomnia patients. This offers an objective depiction of the clinical diagnosis of insomnia, yielding a beneficial impact on the identification of effective biomarkers and the comprehension of insomnia.
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Affiliation(s)
- Jiahui Wu
- College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, China
| | - Jianbo Yang
- Sichuan University of Science and Engineering, Zigong, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau, SAR China
| | - Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China.
| | - Zhiwei Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tianwei Qin
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaoxuan Li
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Hanbin Deng
- Sichuan Institute of Computer Sciences, Chengdu, China.
| | - Liang Gong
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, China.
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2
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Calabro FJ, Parr AC, Sydnor VJ, Hetherington H, Prasad KM, Ibrahim TS, Sarpal DK, Famalette A, Verma P, Luna B. Leveraging ultra-high field (7T) MRI in psychiatric research. Neuropsychopharmacology 2024; 50:85-102. [PMID: 39251774 PMCID: PMC11525672 DOI: 10.1038/s41386-024-01980-6] [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: 04/01/2024] [Revised: 06/21/2024] [Accepted: 07/23/2024] [Indexed: 09/11/2024]
Abstract
Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.
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Affiliation(s)
- Finnegan J Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Ashley C Parr
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Valerie J Sydnor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Konasale M Prasad
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Tamer S Ibrahim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Deepak K Sarpal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alyssa Famalette
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Piya Verma
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
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3
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Haghir H, Kuckertz A, Zhao L, Hami J, Palomero-Gallagher N. A new map of the rat isocortex and proisocortex: cytoarchitecture and M 2 receptor distribution patterns. Brain Struct Funct 2024; 229:1795-1822. [PMID: 37318645 PMCID: PMC11485150 DOI: 10.1007/s00429-023-02654-7] [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: 11/29/2022] [Accepted: 05/13/2023] [Indexed: 06/16/2023]
Abstract
Neurotransmitters and their receptors are key molecules in information transfer between neurons, thus enabling inter-areal communication. Therefore, multimodal atlases integrating the brain's cyto- and receptor architecture constitute crucial tools to understand the relationship between its structural and functional segregation. Cholinergic muscarinic M2 receptors have been shown to be an evolutionarily conserved molecular marker of primary sensory areas in the mammalian brain. To complement existing rodent atlases, we applied a silver cell body staining and quantitative in vitro receptor autoradiographic visualization of M2 receptors to alternating sections throughout the entire brain of five adult male Wistar rats (three sectioned coronally, one horizontally, one sagittally). Histological sections and autoradiographs were scanned at a spatial resolution of 1 µm and 20 µm per pixel, respectively, and files were stored as 8 bit images. We used these high-resolution datasets to create an atlas of the entire rat brain, including the olfactory bulb, cerebellum and brainstem. We describe the cyto- and M2 receptor architectonic features of 48 distinct iso- and proisocortical areas across the rat forebrain and provide their mean M2 receptor density. The ensuing parcellation scheme, which is discussed in the framework of existing comprehensive atlasses, includes the novel subdivision of mediomedial secondary visual area Oc2MM into anterior (Oc2MMa) and posterior (Oc2MMp) parts, and of lateral visual area Oc2L into rostrolateral (Oc2Lr), intermediate dorsolateral (Oc2Lid), intermediate ventrolateral (Oc2Liv) and caudolateral (Oc2Lc) secondary visual areas. The M2 receptor densities and the comprehensive map of iso-and proisocortical areas constitute useful tools for future computational and neuroscientific studies.
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Affiliation(s)
- Hossein Haghir
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
- Department of Anatomy and Cell Biology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Genetic Research Center (MGRC), School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Anika Kuckertz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
| | - Ling Zhao
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
| | - Javad Hami
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
- Faculty of Medicine, HMU Health and Medical University Potsdam, 14471, Potsdam, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany.
- C. & O. Vogt Institute of Brain Research, Heinrich-Heine-University Düsseldorf, 40225, Düsseldorf, Germany.
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Wang J, Gong R, Heidari S, Rogers M, Tani T, Abe H, Ichinohe N, Woodward A, Delmas PJ. A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images. Neuroinformatics 2024:10.1007/s12021-024-09688-0. [PMID: 39417954 DOI: 10.1007/s12021-024-09688-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/27/2024] [Indexed: 10/19/2024]
Abstract
Characterizing the anatomical structure and connectivity between cortical regions is a critical step towards understanding the information processing properties of the brain and will help provide insight into the nature of neurological disorders. A key feature of the mammalian cerebral cortex is its laminar structure. Identifying these layers in neuroimaging data is important for understanding their global structure and to help understand the connectivity patterns of neurons in the brain. We studied Nissl-stained and myelin-stained slice images of the brain of the common marmoset (Callithrix jacchus), which is a new world monkey that is becoming increasingly popular in the neuroscience community as an object of study. We present a novel computational framework that first acquired the cortical labels using AI-based tools followed by a trained deep learning model to segment cerebral cortical layers. We obtained a Euclidean distance of 1274.750 ± 156.400 μ m for the cortical labels acquisition, which was in the acceptable range by computing the half Euclidean distance of the average cortex thickness ( 1800.630 μ m ). We compared our cortical layer segmentation pipeline with the pipeline proposed by Wagstyl et al. (PLoS biology, 18(4), e3000678 2020) adapted to 2D data. We obtained a better mean95 th percentile Hausdorff distance (95HD) of 92.150 μ m . Whereas a mean 95HD of 94.170 μ m was obtained from Wagstyl et al. We also compared our pipeline's performance against theirs using their dataset (the BigBrain dataset). The results also showed better segmentation quality, 85.318 % Jaccard Index acquired from our pipeline, while 83.000 % was stated in their paper.
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Affiliation(s)
- Jiaxuan Wang
- Intelligent Vision Systems Lab, The University of Auckland, Auckland, New Zealand
| | - Rui Gong
- Theoretical Biology Group, Department of Creative Research, Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki, Aichi, 444-8787, Japan
| | - Shahrokh Heidari
- Intelligent Vision Systems Lab, The University of Auckland, Auckland, New Zealand
| | - Mitchell Rogers
- Intelligent Vision Systems Lab, The University of Auckland, Auckland, New Zealand
| | - Toshiki Tani
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Japan
| | - Hiroshi Abe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Japan
| | - Noritaka Ichinohe
- Department of Ultrastructural Research, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Alexander Woodward
- Intelligent Vision Systems Lab, The University of Auckland, Auckland, New Zealand
| | - Patrice J Delmas
- Intelligent Vision Systems Lab, The University of Auckland, Auckland, New Zealand.
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5
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Khan AF, Iturria-Medina Y. Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms. Transl Psychiatry 2024; 14:386. [PMID: 39313512 PMCID: PMC11420368 DOI: 10.1038/s41398-024-03073-w] [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: 02/01/2024] [Revised: 08/20/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024] Open
Abstract
From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.
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Affiliation(s)
- Ahmed Faraz Khan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada.
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada.
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6
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Weber CF, Kebets V, Benkarim O, Lariviere S, Wang Y, Ngo A, Jiang H, Chai X, Park BY, Milham MP, Di Martino A, Valk S, Hong SJ, Bernhardt BC. Contracted functional connectivity profiles in autism. Mol Autism 2024; 15:38. [PMID: 39261969 PMCID: PMC11391747 DOI: 10.1186/s13229-024-00616-2] [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: 04/21/2024] [Accepted: 08/14/2024] [Indexed: 09/13/2024] Open
Abstract
OBJECTIVE Autism spectrum disorder (ASD) is a neurodevelopmental condition that is associated with atypical brain network organization, with prior work suggesting differential connectivity alterations with respect to functional connection length. Here, we tested whether functional connectopathy in ASD specifically relates to disruptions in long- relative to short-range functional connections. Our approach combined functional connectomics with geodesic distance mapping, and we studied associations to macroscale networks, microarchitectural patterns, as well as socio-demographic and clinical phenotypes. METHODS We studied 211 males from three sites of the ABIDE-I dataset comprising 103 participants with an ASD diagnosis (mean ± SD age = 20.8 ± 8.1 years) and 108 neurotypical controls (NT, 19.2 ± 7.2 years). For each participant, we computed cortex-wide connectivity distance (CD) measures by combining geodesic distance mapping with resting-state functional connectivity profiling. We compared CD between ASD and NT participants using surface-based linear models, and studied associations with age, symptom severity, and intelligence scores. We contextualized CD alterations relative to canonical networks and explored spatial associations with functional and microstructural cortical gradients as well as cytoarchitectonic cortical types. RESULTS Compared to NT, ASD participants presented with widespread reductions in CD, generally indicating shorter average connection length and thus suggesting reduced long-range connectivity but increased short-range connections. Peak reductions were localized in transmodal systems (i.e., heteromodal and paralimbic regions in the prefrontal, temporal, and parietal and temporo-parieto-occipital cortex), and effect sizes correlated with the sensory-transmodal gradient of brain function. ASD-related CD reductions appeared consistent across inter-individual differences in age and symptom severity, and we observed a positive correlation of CD to IQ scores. LIMITATIONS Despite rigorous harmonization across the three different acquisition sites, heterogeneity in autism poses a potential limitation to the generalizability of our results. Additionally, we focussed male participants, warranting future studies in more balanced cohorts. CONCLUSIONS Our study showed reductions in CD as a relatively stable imaging phenotype of ASD that preferentially impacted paralimbic and heteromodal association systems. CD reductions in ASD corroborate previous reports of ASD-related imbalance between short-range overconnectivity and long-range underconnectivity.
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Affiliation(s)
- Clara F Weber
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Social Neuroscience Lab, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | - Valeria Kebets
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Oualid Benkarim
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sara Lariviere
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Yezhou Wang
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Hongxiu Jiang
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Xiaoqian Chai
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Bo-Yong Park
- Department of Data Science, Inha University, Incheon, South Korea
- Center for Neuroscience Imaging Research, Institute for Basic Research, Suwon, South Korea
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, USA
| | | | - Sofie Valk
- Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Research, Suwon, South Korea
- Center for the Developing Brain, Child Mind Institute, New York, USA
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
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7
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Castro-Mendoza PB, Weaver CM, Chang W, Medalla M, Rockland KS, Lowery L, McDonough E, Varghese M, Hof PR, Meyer DE, Luebke JI. Proteomic features of gray matter layers and superficial white matter of the rhesus monkey neocortex: comparison of prefrontal area 46 and occipital area 17. Brain Struct Funct 2024; 229:1495-1525. [PMID: 38943018 PMCID: PMC11374833 DOI: 10.1007/s00429-024-02819-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 06/08/2024] [Indexed: 06/30/2024]
Abstract
In this novel large-scale multiplexed immunofluorescence study we comprehensively characterized and compared layer-specific proteomic features within regions of interest of the widely divergent dorsolateral prefrontal cortex (A46) and primary visual cortex (A17) of adult rhesus monkeys. Twenty-eight markers were imaged in rounds of sequential staining, and their spatial distribution precisely quantified within gray matter layers and superficial white matter. Cells were classified as neurons, astrocytes, oligodendrocytes, microglia, or endothelial cells. The distribution of fibers and blood vessels were assessed by quantification of staining intensity across regions of interest. This method revealed multivariate similarities and differences between layers and areas. Protein expression in neurons was the strongest determinant of both laminar and regional differences, whereas protein expression in glia was more important for intra-areal laminar distinctions. Among specific results, we observed a lower glia-to-neuron ratio in A17 than in A46 and the pan-neuronal markers HuD and NeuN were differentially distributed in both brain areas with a lower intensity of NeuN in layers 4 and 5 of A17 compared to A46 and other A17 layers. Astrocytes and oligodendrocytes exhibited distinct marker-specific laminar distributions that differed between regions; notably, there was a high proportion of ALDH1L1-expressing astrocytes and of oligodendrocyte markers in layer 4 of A17. The many nuanced differences in protein expression between layers and regions observed here highlight the need for direct assessment of proteins, in addition to RNA expression, and set the stage for future protein-focused studies of these and other brain regions in normal and pathological conditions.
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Affiliation(s)
- Paola B Castro-Mendoza
- Department of Anatomy and Neurobiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Christina M Weaver
- Department of Mathematics, Franklin and Marshall College, Lancaster, PA, 17604, USA
| | - Wayne Chang
- Yale School of Medicine, 333 Cedar St, New Haven, CT, 06510, USA
| | - Maria Medalla
- Department of Anatomy and Neurobiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Kathleen S Rockland
- Department of Anatomy and Neurobiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Lisa Lowery
- GE HealthCare Technology and Innovation Center, Niskayuna, NY, 12309, USA
| | | | - Merina Varghese
- Nash Family Department of Neuroscience, Friedman Brain Institute, and Center for Discovery and Innovation, Icahn School of Medicine at Mount Sinai, New York, NY, 10019, USA
| | - Patrick R Hof
- Nash Family Department of Neuroscience, Friedman Brain Institute, and Center for Discovery and Innovation, Icahn School of Medicine at Mount Sinai, New York, NY, 10019, USA
| | - Dan E Meyer
- GE HealthCare Technology and Innovation Center, Niskayuna, NY, 12309, USA
| | - Jennifer I Luebke
- Department of Anatomy and Neurobiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA.
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8
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Küchenhoff S, Bayrak Ş, Zsido RG, Saberi A, Bernhardt BC, Weis S, Schaare HL, Sacher J, Eickhoff S, Valk SL. Relating sex-bias in human cortical and hippocampal microstructure to sex hormones. Nat Commun 2024; 15:7279. [PMID: 39179555 PMCID: PMC11344136 DOI: 10.1038/s41467-024-51459-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 07/25/2024] [Indexed: 08/26/2024] Open
Abstract
Determining sex-bias in brain structure is of great societal interest to improve diagnostics and treatment of brain-related disorders. So far, studies on sex-bias in brain structure predominantly focus on macro-scale measures, and often ignore factors determining this bias. Here we study sex-bias in cortical and hippocampal microstructure in relation to sex hormones. Investigating quantitative intracortical profiling in-vivo using the T1w/T2w ratio in 1093 healthy females and males of the cross-sectional Human Connectome Project young adult sample, we find that regional cortical and hippocampal microstructure differs between males and females and that the effect size of this sex-bias varies depending on self-reported hormonal status in females. Microstructural sex-bias and expression of sex hormone genes, based on an independent post-mortem sample, are spatially coupled. Lastly, sex-bias is most pronounced in paralimbic areas, with low laminar complexity, which are predicted to be most plastic based on their cytoarchitectural properties. Albeit correlative, our study underscores the importance of incorporating sex hormone variables into the investigation of brain structure and plasticity.
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Affiliation(s)
- Svenja Küchenhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - Şeyma Bayrak
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Rachel G Zsido
- Cognitive Neuroendocrinology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Amin Saberi
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Susanne Weis
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - H Lina Schaare
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Julia Sacher
- Centre for Integrative Women's Health and Gender Medicine, Medical Faculty & University Hospital Leipzig, Leipzig, Germany
| | - Simon Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sofie L Valk
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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9
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Niu M, Rapan L, Froudist-Walsh S, Zhao L, Funck T, Amunts K, Palomero-Gallagher N. Multimodal mapping of macaque monkey somatosensory cortex. Prog Neurobiol 2024; 239:102633. [PMID: 38830482 DOI: 10.1016/j.pneurobio.2024.102633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 04/19/2024] [Accepted: 05/27/2024] [Indexed: 06/05/2024]
Abstract
The somatosensory cortex is a brain region responsible for receiving and processing sensory information from across the body and is structurally and functionally heterogeneous. Since the chemoarchitectonic segregation of the cerebral cortex can be revealed by transmitter receptor distribution patterns, by using a quantitative multireceptor architectonical analysis, we determined the number and extent of distinct areas of the macaque somatosensory cortex. We identified three architectonically distinct cortical entities within the primary somatosensory cortex (i.e., 3bm, 3bli, 3ble), four within the anterior parietal cortex (i.e., 3am, 3al, 1 and 2) and six subdivisions (i.e., S2l, S2m, PVl, PVm, PRl and PRm) within the lateral fissure. We provide an ultra-high resolution 3D atlas of macaque somatosensory areas in stereotaxic space, which integrates cyto- and receptor architectonic features of identified areas. Multivariate analyses of the receptor fingerprints revealed four clusters of identified areas based on the degree of (dis)similarity of their receptor architecture. Each of these clusters can be associated with distinct levels of somatosensory processing, further demonstrating that the functional segregation of cortical areas is underpinned by differences in their molecular organization.
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Affiliation(s)
- Meiqi Niu
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.
| | - Lucija Rapan
- C. & O. Vogt Institute of Brain Research, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Seán Froudist-Walsh
- Bristol Computational Neuroscience Unit, Faculty of Engineering, University of Bristol, Bristol, UK
| | - Ling Zhao
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Thomas Funck
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; C. & O. Vogt Institute of Brain Research, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; C. & O. Vogt Institute of Brain Research, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
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10
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Cano-Astorga N, Plaza-Alonso S, DeFelipe J, Alonso-Nanclares L. Volume electron microscopy analysis of synapses in primary regions of the human cerebral cortex. Cereb Cortex 2024; 34:bhae312. [PMID: 39106175 DOI: 10.1093/cercor/bhae312] [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: 05/08/2024] [Revised: 07/03/2024] [Accepted: 07/12/2024] [Indexed: 08/09/2024] Open
Abstract
Functional and structural studies investigating macroscopic connectivity in the human cerebral cortex suggest that high-order associative regions exhibit greater connectivity compared to primary ones. However, the synaptic organization of these brain regions remains unexplored. In the present work, we conducted volume electron microscopy to investigate the synaptic organization of the human brain obtained at autopsy. Specifically, we examined layer III of Brodmann areas 17, 3b, and 4, as representative areas of primary visual, somatosensorial, and motor cortex. Additionally, we conducted comparative analyses with our previous datasets of layer III from temporopolar and anterior cingulate associative cortical regions (Brodmann areas 24, 38, and 21). 9,690 synaptic junctions were 3D reconstructed, showing that certain synaptic characteristics are specific to particular regions. The number of synapses per volume, the proportion of the postsynaptic targets, and the synaptic size may distinguish one region from another, regardless of whether they are associative or primary cortex. By contrast, other synaptic characteristics were common to all analyzed regions, such as the proportion of excitatory and inhibitory synapses, their shapes, their spatial distribution, and a higher proportion of synapses located on dendritic spines. The present results provide further insights into the synaptic organization of the human cerebral cortex.
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Affiliation(s)
- Nicolás Cano-Astorga
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- PhD Program in Neuroscience, Autonoma de Madrid University-Cajal Institute, Arzobispo Morcillo 4, Madrid 28029, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Sergio Plaza-Alonso
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Lidia Alonso-Nanclares
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
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11
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Nebli A, Schiffer C, Niu M, Palomero-Gallagher N, Amunts K, Dickscheid T. Generative Modelling of Cortical Receptor Distributions from Cytoarchitectonic Images in the Macaque Brain. Neuroinformatics 2024; 22:389-402. [PMID: 38976151 PMCID: PMC11329581 DOI: 10.1007/s12021-024-09673-7] [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] [Accepted: 06/06/2024] [Indexed: 07/09/2024]
Abstract
Neurotransmitter receptor densities are relevant for understanding the molecular architecture of brain regions. Quantitative in vitro receptor autoradiography, has been introduced to map neurotransmitter receptor distributions of brain areas. However, it is very time and cost-intensive, which makes it challenging to obtain whole-brain distributions. At the same time, high-throughput light microscopy and 3D reconstructions have enabled high-resolution brain maps capturing measures of cell density across the whole human brain. Aiming to bridge gaps in receptor measurements for building detailed whole-brain atlases, we study the feasibility of predicting realistic neurotransmitter density distributions from cell-body stainings. Specifically, we utilize conditional Generative Adversarial Networks (cGANs) to predict the density distributions of the M2 receptor of acetylcholine and the kainate receptor for glutamate in the macaque monkey's primary visual (V1) and motor cortex (M1), based on light microscopic scans of cell-body stained sections. Our model is trained on corresponding patches from aligned consecutive sections that display cell-body and receptor distributions, ensuring a mapping between the two modalities. Evaluations of our cGANs, both qualitative and quantitative, show their capability to predict receptor densities from cell-body stained sections while maintaining cortical features such as laminar thickness and curvature. Our work underscores the feasibility of cross-modality image translation problems to address data gaps in multi-modal brain atlases.
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Affiliation(s)
- Ahmed Nebli
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.
- Helmholtz AI, Research Centre Jülich, Jülich, Germany.
| | - Christian Schiffer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Helmholtz AI, Research Centre Jülich, Jülich, Germany
| | - Meiqi Niu
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile & Oscar Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile & Oscar Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Timo Dickscheid
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Helmholtz AI, Research Centre Jülich, Jülich, Germany
- Institute of Computer Science, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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12
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Leontyev D, Pulliam AN, Ma X, Gaul DA, LaPlaca MC, Fernández FM. Spatial lipidomics maps brain alterations associated with mild traumatic brain injury. Front Chem 2024; 12:1394064. [PMID: 38873407 PMCID: PMC11169706 DOI: 10.3389/fchem.2024.1394064] [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: 02/29/2024] [Accepted: 05/07/2024] [Indexed: 06/15/2024] Open
Abstract
Traumatic brain injury (TBI) is a global public health problem with 50-60 million incidents per year, most of which are considered mild (mTBI) and many of these repetitive (rmTBI). Despite their massive implications, the pathologies of mTBI and rmTBI are not fully understood, with a paucity of information on brain lipid dysregulation following mild injury event(s). To gain more insight on mTBI and rmTBI pathology, a non-targeted spatial lipidomics workflow utilizing high resolution mass spectrometry imaging was developed to map brain region-specific lipid alterations in rats following injury. Discriminant multivariate models were created for regions of interest including the hippocampus, cortex, and corpus callosum to pinpoint lipid species that differentiated between injured and sham animals. A multivariate model focused on the hippocampus region differentiated injured brain tissues with an area under the curve of 0.99 using only four lipid species. Lipid classes that were consistently discriminant included polyunsaturated fatty acid-containing phosphatidylcholines (PC), lysophosphatidylcholines (LPC), LPC-plasmalogens (LPC-P) and PC potassium adducts. Many of the polyunsaturated fatty acid-containing PC and LPC-P selected have never been previously reported as altered in mTBI. The observed lipid alterations indicate that neuroinflammation and oxidative stress are important pathologies that could serve to explain cognitive deficits associated with rmTBI. Therapeutics which target or attenuate these pathologies may be beneficial to limit persistent damage following a mild brain injury event.
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Affiliation(s)
- Dmitry Leontyev
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, United States
| | - Alexis N. Pulliam
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology/Emory University, Atlanta, GA, United States
| | - Xin Ma
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, United States
| | - David A. Gaul
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, United States
- Parker H. Petit Institute for Bioengineering and Bioscience, Atlanta, GA, United States
| | - Michelle C. LaPlaca
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology/Emory University, Atlanta, GA, United States
- Parker H. Petit Institute for Bioengineering and Bioscience, Atlanta, GA, United States
| | - Facundo M. Fernández
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, United States
- Parker H. Petit Institute for Bioengineering and Bioscience, Atlanta, GA, United States
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13
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Báez-Yáñez MG, Schellekens W, Bhogal AA, Roefs ECA, van Osch MJP, Siero JCW, Petridou N. A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595716. [PMID: 38826311 PMCID: PMC11142244 DOI: 10.1101/2024.05.24.595716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Wouter Schellekens
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Donders Centre for Cognitive Neuroimaging, Radboud UMC, Nijmegen, Netherlands
| | - Alex A Bhogal
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Emiel C A Roefs
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jeroen C W Siero
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Natalia Petridou
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
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14
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Mueller SG. 7T MP2RAGE for cortical myelin segmentation: Impact of aging. PLoS One 2024; 19:e0299670. [PMID: 38626149 PMCID: PMC11020839 DOI: 10.1371/journal.pone.0299670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 02/14/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND Myelin and iron are major contributors to the cortical MR signal. The aim of this study was to investigate 1. Can MP2RAGE-derived contrasts at 7T in combination with k-means clustering be used to distinguish between heavily and sparsely myelinated layers in cortical gray matter (GM)? 2. Does this approach provide meaningful biological information? METHODS The following contrasts were generated from the 7T MP2RAGE images from 45 healthy controls (age: 19-75, f/m = 23/22) from the ATAG data repository: 1. T1 weighted image (UNI). 2. T1 relaxation image (T1map). 3. INVC/T1map ratio (RATIO). K-means clustering identified 6 clusters/tissue maps (csf, csf/gm-transition, wm, wm/gm transition, heavily myelinated cortical GM (dGM), sparsely myelinated cortical GM (sGM)). These tissue maps were then processed with SPM/DARTEL (volume-based analyses) and Freesurfer (surface-based analyses) and dGM and sGM volume/thickness of young adults (n = 27, 19-27 years) compared to those of older adults (n = 18, 42-75 years) at p<0.001 uncorrected. RESULTS The resulting maps showed good agreement with histological maps in the literature. Volume- and surface analyses found age-related dGM loss/thinning in the mid-posterior cingulate and parahippocampal/entorhinal gyrus and age-related sGM losses in lateral, mesial and orbitofrontal frontal, insular cortex and superior temporal gyrus. CONCLUSION The MP2RAGE derived UNI, T1map and RATIO contrasts can be used to identify dGM and sGM. Considering the close relationship between cortical myelo- and cytoarchitecture, the findings reported here indicate that this new technique might provide new insights into the nature of cortical GM loss in physiological and pathological conditions.
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Affiliation(s)
- Susanne G. Mueller
- Dept. of Radiology, University of California, San Francisco, San Francisco, CA, United States of America
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15
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Zhou Y, He W, Hou W, Zhu Y. Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics. Nat Commun 2024; 15:2848. [PMID: 38565531 PMCID: PMC11271244 DOI: 10.1038/s41467-024-47152-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/20/2024] [Indexed: 04/04/2024] Open
Abstract
Spatial transcriptomics has revolutionized the study of gene expression within tissues, while preserving spatial context. However, annotating spatial spots' biological identity remains a challenge. To tackle this, we introduce Pianno, a Bayesian framework automating structural semantics annotation based on marker genes. Comprehensive evaluations underscore Pianno's remarkable prowess in precisely annotating a wide array of spatial semantics, ranging from diverse anatomical structures to intricate tumor microenvironments, as well as in estimating cell type distributions, across data generated from various spatial transcriptomics platforms. Furthermore, Pianno, in conjunction with clustering approaches, uncovers a region- and species-specific excitatory neuron subtype in the deep layer 3 of the human neocortex, shedding light on cellular evolution in the human neocortex. Overall, Pianno equips researchers with a robust and efficient tool for annotating diverse biological structures, offering new perspectives on spatial transcriptomics data.
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Affiliation(s)
- Yuqiu Zhou
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Wei He
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Weizhen Hou
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
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16
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McManus E, Muhlert N, Duncan NW. InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels. Neuroinformatics 2024; 22:135-145. [PMID: 38386228 DOI: 10.1007/s12021-024-09654-w] [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] [Accepted: 12/21/2023] [Indexed: 02/23/2024]
Abstract
Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and γ -aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABA- and glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool - InSpectro-Gadget - that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use is demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget .
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Affiliation(s)
| | - Nils Muhlert
- School of Health Sciences, University of Manchester, Manchester, UK
| | - Niall W Duncan
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
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17
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Leontyev D, Pulliam AN, Ma X, Gaul DA, LaPlaca MC, Fernandez FM. Spatial Lipidomics Maps Brain Alterations Associated with Mild Traumatic Brain Injury. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.25.577203. [PMID: 38328252 PMCID: PMC10849710 DOI: 10.1101/2024.01.25.577203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Traumatic brain injury (TBI) is a global public health problem with 50-60 million incidents per year, most of which are considered mild (mTBI) and many of these repetitive (rmTBI). Despite their massive implications, the pathologies of mTBI and rmTBI are not fully understood, with a paucity of information on brain lipid dysregulation following mild injury event(s). To gain more insight on mTBI and rmTBI pathology, a non-targeted spatial lipidomics workflow utilizing ultrahigh resolution mass spectrometry imaging was developed to map brain region-specific lipid alterations in rats following injury. Discriminant multivariate models were created for regions of interest including the hippocampus, cortex, and corpus callosum to pinpoint lipid species that differentiated between injured and sham animals. A multivariate model focused on the hippocampus region differentiated injured brain tissues with an area under the curve of 0.994 using only four lipid species. Lipid classes that were consistently discriminant included polyunsaturated fatty acid-containing phosphatidylcholines (PC), lysophosphatidylcholines (LPC), LPC-plasmalogens (LPC-P) and PC potassium adducts. Many of the polyunsaturated fatty acid-containing PC and LPC-P selected have never been previously reported as altered in mTBI. The observed lipid alterations indicate that neuroinflammation, oxidative stress and disrupted sodium-potassium pumps are important pathologies that could serve to explain cognitive deficits associated with rmTBI. Therapeutics which target or attenuate these pathologies may be beneficial to limit persistent damage following a mild brain injury event.
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18
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Shamir I, Assaf Y, Shamir R. Clustering the cortical laminae: in vivo parcellation. Brain Struct Funct 2024; 229:443-458. [PMID: 38193916 PMCID: PMC10917860 DOI: 10.1007/s00429-023-02748-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/04/2023] [Indexed: 01/10/2024]
Abstract
The laminar microstructure of the cerebral cortex has distinct anatomical characteristics of the development, function, connectivity, and even various pathologies of the brain. In recent years, multiple neuroimaging studies have utilized magnetic resonance imaging (MRI) relaxometry to visualize and explore this intricate microstructure, successfully delineating the cortical laminar components. Despite this progress, T1 is still primarily considered a direct measure of myeloarchitecture (myelin content), rather than a probe of tissue cytoarchitecture (cellular composition). This study aims to offer a robust, whole-brain validation of T1 imaging as a practical and effective tool for exploring the laminar composition of the cortex. To do so, we cluster complex microstructural cortical datasets of both human (N = 30) and macaque (N = 1) brains using an adaptation of an algorithm for clustering cell omics profiles. The resulting cluster patterns are then compared to established atlases of cytoarchitectonic features, exhibiting significant correspondence in both species. Lastly, we demonstrate the expanded applicability of T1 imaging by exploring some of the cytoarchitectonic features behind various unique skillsets, such as musicality and athleticism.
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Affiliation(s)
- Ittai Shamir
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
| | - Yaniv Assaf
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Ron Shamir
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
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19
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Wagstyl K, Adler S, Seidlitz J, Vandekar S, Mallard TT, Dear R, DeCasien AR, Satterthwaite TD, Liu S, Vértes PE, Shinohara RT, Alexander-Bloch A, Geschwind DH, Raznahan A. Transcriptional cartography integrates multiscale biology of the human cortex. eLife 2024; 12:RP86933. [PMID: 38324465 PMCID: PMC10945526 DOI: 10.7554/elife.86933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.
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Affiliation(s)
- Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Sophie Adler
- UCL Great Ormond Street Institute for Child HealthHolbornUnited Kingdom
| | - Jakob Seidlitz
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt UniversityNashvilleUnited States
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General HospitalBostonUnited States
- Department of Psychiatry, Harvard Medical SchoolBostonUnited States
| | - Richard Dear
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Alex R DeCasien
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of MedicinePhiladelphiaUnited States
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Petra E Vértes
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Daniel H Geschwind
- Center for Autism Research and Treatment, Semel Institute, Program in Neurogenetics, Department of Neurology and Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
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20
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Frigerio I, Bouwman MMA, Noordermeer RTGMM, Podobnik E, Popovic M, Timmermans E, Rozemuller AJM, van de Berg WDJ, Jonkman LE. Regional differences in synaptic degeneration are linked to alpha-synuclein burden and axonal damage in Parkinson's disease and dementia with Lewy bodies. Acta Neuropathol Commun 2024; 12:4. [PMID: 38173031 PMCID: PMC10765668 DOI: 10.1186/s40478-023-01711-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Regional differences in synaptic degeneration may underlie differences in clinical presentation and neuropathological disease progression in Parkinson's Disease (PD) and Dementia with Lewy bodies (DLB). Here, we mapped and quantified synaptic degeneration in cortical brain regions in PD, PD with dementia (PDD) and DLB, and assessed whether regional differences in synaptic loss are linked to axonal degeneration and neuropathological burden. We included a total of 47 brain donors, 9 PD, 12 PDD, 6 DLB and 20 non-neurological controls. Synaptophysin+ and SV2A+ puncta were quantified in eight cortical regions using a high throughput microscopy approach. Neurofilament light chain (NfL) immunoreactivity, Lewy body (LB) density, phosphorylated-tau and amyloid-β load were also quantified. Group differences in synaptic density, and associations with neuropathological markers and Clinical Dementia Rating (CDR) scores, were investigated using linear mixed models. We found significantly decreased synaptophysin and SV2A densities in the cortex of PD, PDD and DLB cases compared to controls. Specifically, synaptic density was decreased in cortical regions affected at Braak α-synuclein stage 5 in PD (middle temporal gyrus, anterior cingulate and insula), and was additionally decreased in cortical regions affected at Braak α-synuclein stage 4 in PDD and DLB compared to controls (entorhinal cortex, parahippocampal gyrus and fusiform gyrus). Synaptic loss associated with higher NfL immunoreactivity and LB density. Global synaptophysin loss associated with longer disease duration and higher CDR scores. Synaptic neurodegeneration occurred in temporal, cingulate and insular cortices in PD, as well as in parahippocampal regions in PDD and DLB. In addition, synaptic loss was linked to axonal damage and severe α-synuclein burden. These results, together with the association between synaptic loss and disease progression and cognitive impairment, indicate that regional synaptic loss may underlie clinical differences between PD and PDD/DLB. Our results might provide useful information for the interpretation of synaptic biomarkers in vivo.
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Affiliation(s)
- Irene Frigerio
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Brain imaging, Amsterdam, The Netherlands.
| | - Maud M A Bouwman
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain imaging, Amsterdam, The Netherlands
| | - Ruby T G M M Noordermeer
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands
| | - Ema Podobnik
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands
| | - Marko Popovic
- Department Molecular cell biology & Immunology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Evelien Timmermans
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands
| | - Annemieke J M Rozemuller
- Department of Pathology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Section Clinical Neuroanatomy and Biobanking, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, 1081 HV, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain imaging, Amsterdam, The Netherlands
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21
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Nolan M, Scott C, Hof PR, Ansorge O. Betz cells of the primary motor cortex. J Comp Neurol 2024; 532:e25567. [PMID: 38289193 PMCID: PMC10952528 DOI: 10.1002/cne.25567] [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: 08/09/2023] [Revised: 11/11/2023] [Accepted: 11/17/2023] [Indexed: 02/01/2024]
Abstract
Betz cells, named in honor of Volodymyr Betz (1834-1894), who described them as "giant pyramids" in the primary motor cortex of primates and other mammalian species, are layer V extratelencephalic projection (ETP) neurons that directly innervate α-motoneurons of the brainstem and spinal cord. Despite their large volume and circumferential dendritic architecture, to date, no single molecular criterion has been established that unequivocally distinguishes adult Betz cells from other layer V ETP neurons. In primates, transcriptional signatures suggest the presence of at least two ETP neuron clusters that contain mature Betz cells; these are characterized by an abundance of axon guidance and oxidative phosphorylation transcripts. How neurodevelopmental programs drive the distinct positional and morphological features of Betz cells in humans remains unknown. Betz cells display a distinct biphasic firing pattern involving early cessation of firing followed by delayed sustained acceleration in spike frequency and magnitude. Few cell type-specific transcripts and electrophysiological characteristics are conserved between rodent layer V ETP neurons of the motor cortex and primate Betz cells. This has implications for the modeling of disorders that affect the motor cortex in humans, such as amyotrophic lateral sclerosis (ALS). Perhaps vulnerability to ALS is linked to the evolution of neural networks for fine motor control reflected in the distinct morphomolecular architecture of the human motor cortex, including Betz cells. Here, we discuss histological, molecular, and functional data concerning the position of Betz cells in the emerging taxonomy of neurons across diverse species and their role in neurological disorders.
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Affiliation(s)
- Matthew Nolan
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Connor Scott
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Patrick. R. Hof
- Nash Family Department of Neuroscience and Friedman Brain InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Olaf Ansorge
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
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22
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Kruggel F, Solodkin A. Analyzing the cortical fine structure as revealed by ex-vivo anatomical MRI. J Comp Neurol 2023; 531:2146-2161. [PMID: 37522626 DOI: 10.1002/cne.25532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 04/15/2023] [Accepted: 06/21/2023] [Indexed: 08/01/2023]
Abstract
The human cortex has a rich fiber structure as revealed by myelin-staining of histological slices. Myelin also contributes to the image contrast in Magnetic Resonance Imaging (MRI). Recent advances in Magnetic Resonance (MR) scanner and imaging technology allowed the acquisition of an ex-vivo data set at an isotropic resolution of 100 µm. This study focused on a computational analysis of this data set with the aim of bridging between histological knowledge and MRI-based results. This work highlights: (1) the design and implementation of a processing chain that extracts intracortical features from a high-resolution MR image; (2) a demonstration of the correspondence between MRI-based cortical intensity profiles and the myelo-architectonic layering of the cortex; (3) the characterization and classification of four basic myelo-architectonic profile types; (4) the distinction of cortical regions based on myelo-architectonic features; and (5) the segmentation of cortical modules in the entorhinal cortex.
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Affiliation(s)
- Frithjof Kruggel
- Department of Biomedical Engineering, University of California, Irvine, Irvine, California, USA
| | - Ana Solodkin
- School of Behavioral and Brain Sciences, University of Texas, Richardson, Texas, USA
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23
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Saberi A, Paquola C, Wagstyl K, Hettwer MD, Bernhardt BC, Eickhoff SB, Valk SL. The regional variation of laminar thickness in the human isocortex is related to cortical hierarchy and interregional connectivity. PLoS Biol 2023; 21:e3002365. [PMID: 37943873 PMCID: PMC10684102 DOI: 10.1371/journal.pbio.3002365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 11/28/2023] [Accepted: 10/06/2023] [Indexed: 11/12/2023] Open
Abstract
The human isocortex consists of tangentially organized layers with unique cytoarchitectural properties. These layers show spatial variations in thickness and cytoarchitecture across the neocortex, which is thought to support function through enabling targeted corticocortical connections. Here, leveraging maps of the 6 cortical layers based on 3D human brain histology, we aimed to quantitatively characterize the systematic covariation of laminar structure in the cortex and its functional consequences. After correcting for the effect of cortical curvature, we identified a spatial pattern of changes in laminar thickness covariance from lateral frontal to posterior occipital regions, which differentiated the dominance of infra- versus supragranular layer thickness. Corresponding to the laminar regularities of cortical connections along cortical hierarchy, the infragranular-dominant pattern of laminar thickness was associated with higher hierarchical positions of regions, mapped based on resting-state effective connectivity in humans and tract-tracing of structural connections in macaques. Moreover, we show that regions with similar laminar thickness patterns have a higher likelihood of structural connections and strength of functional connections. In sum, here we characterize the organization of laminar thickness in the human isocortex and its association with cortico-cortical connectivity, illustrating how laminar organization may provide a foundational principle of cortical function.
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Affiliation(s)
- Amin Saberi
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Casey Paquola
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | - Konrad Wagstyl
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Meike D. Hettwer
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Max Planck School of Cognition, Leipzig, Germany
| | - Boris C. Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Simon B. Eickhoff
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sofie L. Valk
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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24
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Liao Z, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Papadopoulos Orfanos D, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Paus T. Hemispheric asymmetry in cortical thinning reflects intrinsic organization of the neurotransmitter systems and homotopic functional connectivity. Proc Natl Acad Sci U S A 2023; 120:e2306990120. [PMID: 37831741 PMCID: PMC10589642 DOI: 10.1073/pnas.2306990120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 09/07/2023] [Indexed: 10/15/2023] Open
Abstract
Hemispheric lateralization and its origins have been of great interest in neuroscience for over a century. The left-right asymmetry in cortical thickness may stem from differential maturation of the cerebral cortex in the two hemispheres. Here, we investigated the spatial pattern of hemispheric differences in cortical thinning during adolescence, and its relationship with the density of neurotransmitter receptors and homotopic functional connectivity. Using longitudinal data from IMAGEN study (N = 532), we found that many cortical regions in the frontal and temporal lobes thinned more in the right hemisphere than in the left. Conversely, several regions in the occipital and parietal lobes thinned less in the right (vs. left) hemisphere. We then revealed that regions thinning more in the right (vs. left) hemispheres had higher density of neurotransmitter receptors and transporters in the right (vs. left) side. Moreover, the hemispheric differences in cortical thinning were predicted by homotopic functional connectivity. Specifically, regions with stronger homotopic functional connectivity showed a more symmetrical rate of cortical thinning between the left and right hemispheres, compared with regions with weaker homotopic functional connectivity. Based on these findings, we suggest that the typical patterns of hemispheric differences in cortical thinning may reflect the intrinsic organization of the neurotransmitter systems and related patterns of homotopic functional connectivity.
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Affiliation(s)
- Zhijie Liao
- Research Centre of Sainte-Justine University Hospital, Montreal, QCH3T 1C5, Canada
- Department of Psychiatry and Addictology, University of Montreal, Montreal, QCH3T 1J4, Canada
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
| | - Arun L. W. Bokde
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Social, Genetic & Developmental Psychiatry Centre, King’s College London, LondonSE5 8AF, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim69117, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim68131, Germany
| | - Antoine Grigis
- NeuroSpin, Energies and Atomic Energy Commission, Université Paris-Saclay, Paris F-91191, France
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT05405
- Department of Psychology, University of Vermont, Burlington, VT05405
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, NottinghamNG7 2RD, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin10117, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin38116, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, AP-HP.Sorbonne Université, Paris75006, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
- Etablissement Public de Santé Barthélemy Durand, Paris91700, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim69117, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel24118, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen37075, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden01087, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden01087, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin10117, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Institute for Science and Technology of Brain-inspired Intelligence, Fudan University, Shanghai200437, Peoples Republic of China
- Centre for Population Neuroscience and Precision Medicine, Charite Universitätsmedizin Berlin, Berlin10117, Germany
| | - Tomáš Paus
- Research Centre of Sainte-Justine University Hospital, Montreal, QCH3T 1C5, Canada
- Department of Psychiatry and Addictology, University of Montreal, Montreal, QCH3T 1J4, Canada
- Department of Neuroscience, University of Montreal, Montreal, QCH3T 1J4, Canada
| | - IMAGEN Consortium
- Research Centre of Sainte-Justine University Hospital, Montreal, QCH3T 1C5, Canada
- Department of Psychiatry and Addictology, University of Montreal, Montreal, QCH3T 1J4, Canada
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Social, Genetic & Developmental Psychiatry Centre, King’s College London, LondonSE5 8AF, United Kingdom
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim69117, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim68131, Germany
- NeuroSpin, Energies and Atomic Energy Commission, Université Paris-Saclay, Paris F-91191, France
- Department of Psychiatry, University of Vermont, Burlington, VT05405
- Department of Psychology, University of Vermont, Burlington, VT05405
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, NottinghamNG7 2RD, United Kingdom
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin10117, Germany
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin38116, Germany
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, AP-HP.Sorbonne Université, Paris75006, France
- Etablissement Public de Santé Barthélemy Durand, Paris91700, France
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel24118, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen37075, Germany
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden01087, Germany
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, DublinD02 PN40, Ireland
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Institute for Science and Technology of Brain-inspired Intelligence, Fudan University, Shanghai200437, Peoples Republic of China
- Centre for Population Neuroscience and Precision Medicine, Charite Universitätsmedizin Berlin, Berlin10117, Germany
- Department of Neuroscience, University of Montreal, Montreal, QCH3T 1J4, Canada
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25
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Hansen JY, Shafiei G, Voigt K, Liang EX, Cox SML, Leyton M, Jamadar SD, Misic B. Integrating multimodal and multiscale connectivity blueprints of the human cerebral cortex in health and disease. PLoS Biol 2023; 21:e3002314. [PMID: 37747886 PMCID: PMC10553842 DOI: 10.1371/journal.pbio.3002314] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 10/05/2023] [Accepted: 08/28/2023] [Indexed: 09/27/2023] Open
Abstract
The brain is composed of disparate neural populations that communicate and interact with one another. Although fiber bundles, similarities in molecular architecture, and synchronized neural activity all reflect how brain regions potentially interact with one another, a comprehensive study of how all these interregional relationships jointly reflect brain structure and function remains missing. Here, we systematically integrate 7 multimodal, multiscale types of interregional similarity ("connectivity modes") derived from gene expression, neurotransmitter receptor density, cellular morphology, glucose metabolism, haemodynamic activity, and electrophysiology in humans. We first show that for all connectivity modes, feature similarity decreases with distance and increases when regions are structurally connected. Next, we show that connectivity modes exhibit unique and diverse connection patterns, hub profiles, spatial gradients, and modular organization. Throughout, we observe a consistent primacy of molecular connectivity modes-namely correlated gene expression and receptor similarity-that map onto multiple phenomena, including the rich club and patterns of abnormal cortical thickness across 13 neurological, psychiatric, and neurodevelopmental disorders. Finally, to construct a single multimodal wiring map of the human cortex, we fuse all 7 connectivity modes and show that the fused network maps onto major organizational features of the cortex including structural connectivity, intrinsic functional networks, and cytoarchitectonic classes. Altogether, this work contributes to the integrative study of interregional relationships in the human cerebral cortex.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Katharina Voigt
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Emma X. Liang
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | | | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, Canada
- Department of Psychiatry, McGill University, Montréal, Canada
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Canada
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26
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Kumagai S, Shiramatsu TI, Matsumura A, Ishishita Y, Ibayashi K, Onuki Y, Kawai K, Takahashi H. Frequency-specific modulation of oscillatory activity in the rat auditory cortex by vagus nerve stimulation. Brain Stimul 2023; 16:1476-1485. [PMID: 37777110 DOI: 10.1016/j.brs.2023.09.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 09/21/2023] [Accepted: 09/21/2023] [Indexed: 10/02/2023] Open
Abstract
BACKGROUND We previously found that vagus nerve stimulation (VNS) strengthened stimulus-evoked activity in the superficial layer of the sensory cortex but not in the deep layer, suggesting that VNS altered the balance between the feedforward (FF) and feedback (FB) pathways. Band-specific oscillatory activities in the cortex could serve as an index of the FF-FB balance, but whether VNS affects cortical oscillations along sensory pathways through neuromodulators remains unclear. HYPOTHESIS VNS modulates the FF-FB balance through the cholinergic and noradrenergic systems, which modulate stimulus gain in the cortex. METHODS We investigated the effects of VNS using electrocorticography in the auditory cortex of 34 Wistar rats under general anesthesia while presenting click stimuli. In the time-frequency analyses, the putative modulation of the FF and FB pathways was estimated using high- and low-frequency power. We assessed, using analysis of variance, how VNS modulates auditory-evoked activities and how the modulation changes with cholinergic and noradrenergic antagonists. RESULTS VNS increased auditory cortical evoked potentials, consistent with results of our previous work. Furthermore, VNS increased auditory-evoked gamma and beta powers and decreased theta power. Local administration of cholinergic antagonists in the auditory cortex selectively disrupted the VNS-induced increase in gamma and beta power, while noradrenergic antagonists disrupted the decrease in theta power. CONCLUSIONS VNS might strengthen the FF pathway through the cholinergic system and attenuate the FB pathway through the noradrenergic system in the auditory cortex. Cortical gain modulation through the VNS-induced neuromodulatory system provides new mechanistic insights into the effect of VNS on auditory processing.
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Affiliation(s)
- Shinichi Kumagai
- Department of Neurosurgery, Jichi Medical University, Tochigi, Japan; Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Tomoyo Isoguchi Shiramatsu
- Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Akane Matsumura
- Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Yohei Ishishita
- Department of Neurosurgery, Jichi Medical University, Tochigi, Japan
| | - Kenji Ibayashi
- Department of Neurosurgery, Jichi Medical University, Tochigi, Japan
| | - Yoshiyuki Onuki
- Department of Neurosurgery, Jichi Medical University, Tochigi, Japan
| | - Kensuke Kawai
- Department of Neurosurgery, Jichi Medical University, Tochigi, Japan
| | - Hirokazu Takahashi
- Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
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27
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Cano-Astorga N, Plaza-Alonso S, DeFelipe J, Alonso-Nanclares L. 3D synaptic organization of layer III of the human anterior cingulate and temporopolar cortex. Cereb Cortex 2023; 33:9691-9708. [PMID: 37455478 PMCID: PMC10472499 DOI: 10.1093/cercor/bhad232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
The human anterior cingulate and temporopolar cortices have been proposed as highly connected nodes involved in high-order cognitive functions, but their synaptic organization is still basically unknown due to the difficulties involved in studying the human brain. Using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) to study the synaptic organization of the human brain obtained with a short post-mortem delay allows excellent results to be obtained. We have used this technology to analyze layer III of the anterior cingulate cortex (Brodmann area 24) and the temporopolar cortex, including the temporal pole (Brodmann area 38 ventral and dorsal) and anterior middle temporal gyrus (Brodmann area 21). Our results, based on 6695 synaptic junctions fully reconstructed in 3D, revealed that Brodmann areas 24, 21 and ventral area 38 showed similar synaptic density and synaptic size, whereas dorsal area 38 displayed the highest synaptic density and the smallest synaptic size. However, the proportion of the different types of synapses (excitatory and inhibitory), the postsynaptic targets, and the shapes of excitatory and inhibitory synapses were similar, regardless of the region examined. These observations indicate that certain aspects of the synaptic organization are rather homogeneous, whereas others show specific variations across cortical regions.
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Affiliation(s)
- Nicolás Cano-Astorga
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
- PhD Program in Neuroscience, Autonoma de Madrid University - Cajal Institute, 28029 Madrid, Spain
| | - Sergio Plaza-Alonso
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, 28031 Madrid, Spain
| | - Lidia Alonso-Nanclares
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, 28031 Madrid, Spain
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Rapan L, Froudist-Walsh S, Niu M, Xu T, Zhao L, Funck T, Wang XJ, Amunts K, Palomero-Gallagher N. Cytoarchitectonic, receptor distribution and functional connectivity analyses of the macaque frontal lobe. eLife 2023; 12:e82850. [PMID: 37578332 PMCID: PMC10425179 DOI: 10.7554/elife.82850] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 06/14/2023] [Indexed: 08/15/2023] Open
Abstract
Based on quantitative cyto- and receptor architectonic analyses, we identified 35 prefrontal areas, including novel subdivisions of Walker's areas 10, 9, 8B, and 46. Statistical analysis of receptor densities revealed regional differences in lateral and ventrolateral prefrontal cortex. Indeed, structural and functional organization of subdivisions encompassing areas 46 and 12 demonstrated significant differences in the interareal levels of α2 receptors. Furthermore, multivariate analysis included receptor fingerprints of previously identified 16 motor areas in the same macaque brains and revealed 5 clusters encompassing frontal lobe areas. We used the MRI datasets from the non-human primate data sharing consortium PRIME-DE to perform functional connectivity analyses using the resulting frontal maps as seed regions. In general, rostrally located frontal areas were characterized by bigger fingerprints, that is, higher receptor densities, and stronger regional interconnections. Whereas more caudal areas had smaller fingerprints, but showed a widespread connectivity pattern with distant cortical regions. Taken together, this study provides a comprehensive insight into the molecular structure underlying the functional organization of the cortex and, thus, reconcile the discrepancies between the structural and functional hierarchical organization of the primate frontal lobe. Finally, our data are publicly available via the EBRAINS and BALSA repositories for the entire scientific community.
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Affiliation(s)
- Lucija Rapan
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Sean Froudist-Walsh
- Center for Neural Science, New York UniversityNew YorkUnited States
- Bristol Computational Neuroscience Unit, Faculty of Engineering, University of BristolBristolUnited Kingdom
| | - Meiqi Niu
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Ting Xu
- Center for the Developing Brain, Child Mind InstituteNew YorkUnited States
| | - Ling Zhao
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Thomas Funck
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Xiao-Jing Wang
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Katrin Amunts
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
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29
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Zhang W, Liu N, Zhao Y, Yao C, Yang D, Yang C, Sun H, Wei X, Sweeney JA, Liang H, Zhang M, Gong Q, Lui S. The acute effects of repetitive transcranial magnetic stimulation on laminar diffusion anisotropy of neocortical gray matter. MedComm (Beijing) 2023; 4:e335. [PMID: 37560755 PMCID: PMC10407029 DOI: 10.1002/mco2.335] [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: 02/10/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 08/11/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is increasingly used to treat neuropsychiatric disorders. Inhibitory and excitatory regimens have been both adopted but the exact mechanism of action remains unclear, and investigating their differential effects on laminar diffusion profiles of neocortex may add important evidence. Twenty healthy participants were randomly assigned to receive a low-frequency/inhibitory or high-frequency/excitatory rTMS targeting the left dorsolateral prefrontal cortex (DLPFC). With the brand-new submillimeter diffusion tensor imaging of whole brain and specialized surface-based laminar analysis, fractional anisotropy (FA) and mean diffusion (MD) profiles of cortical layers at different cortical depths were characterized before/after rTMS. Inhibitory and excitatory rTMS both showed impacts on diffusion metrics of somatosensory, limbic, and sensory regions, but different patterns of changes were observed-increased FA with inhibitory rTMS, whereas decreased FA with excitatory rTMS. More importantly, laminar analysis indicated laminar specificity of changes in somatosensory regions during different rTMS patterns-inhibitory rTMS affected the superficial layers contralateral to the DLPFC, while excitatory rTMS led to changes in the intermediate/deep layers bilateral to the DLPFC. These findings provide novel insights into acute neurobiological effects on diffusion profiles of rTMS that may add critical evidence relevant to different protocols of rTMS on neocortex.
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Affiliation(s)
- Wenjing Zhang
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Naici Liu
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Youjin Zhao
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Chenyang Yao
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Dan Yang
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
| | - Chengmin Yang
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Hui Sun
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Xia Wei
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - John A. Sweeney
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Department of Psychiatry and Behavioral NeuroscienceUniversity of Cincinnati College of MedicineCincinnatiOhioUSA
| | | | | | - Qiyong Gong
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
- Department of RadiologyWest China Xiamen Hospital of Sichuan UniversityXiamenFujianChina
| | - Su Lui
- Department of Radiologyand Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China Hospital of Sichuan UniversityChengduChina
- Huaxi MR Research Center (HMRRC)West China Hospital of Sichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
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30
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Shine JM. Neuromodulatory control of complex adaptive dynamics in the brain. Interface Focus 2023; 13:20220079. [PMID: 37065268 PMCID: PMC10102735 DOI: 10.1098/rsfs.2022.0079] [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: 12/05/2022] [Accepted: 01/23/2023] [Indexed: 04/18/2023] Open
Abstract
How is the massive dimensionality and complexity of the microscopic constituents of the nervous system brought under sufficiently tight control so as to coordinate adaptive behaviour? A powerful means for striking this balance is to poise neurons close to the critical point of a phase transition, at which a small change in neuronal excitability can manifest a nonlinear augmentation in neuronal activity. How the brain could mediate this critical transition is a key open question in neuroscience. Here, I propose that the different arms of the ascending arousal system provide the brain with a diverse set of heterogeneous control parameters that can be used to modulate the excitability and receptivity of target neurons-in other words, to act as control parameters for mediating critical neuronal order. Through a series of worked examples, I demonstrate how the neuromodulatory arousal system can interact with the inherent topological complexity of neuronal subsystems in the brain to mediate complex adaptive behaviour.
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Affiliation(s)
- James M. Shine
- Brain and Mind Center, The University of Sydney, Sydney, Australia
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31
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Pais-Roldán P, Yun SD, Palomero-Gallagher N, Shah NJ. Cortical depth-dependent human fMRI of resting-state networks using EPIK. Front Neurosci 2023; 17:1151544. [PMID: 37274214 PMCID: PMC10232833 DOI: 10.3389/fnins.2023.1151544] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/26/2023] [Indexed: 06/06/2023] Open
Abstract
Introduction Recent laminar-fMRI studies have substantially improved understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear. Methods Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers. Results Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest). Discussion The identification of varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) has major implications for the characterization of network-related diseases and suggests the potential diagnostic value of laminar fMRI in psychiatric disorders, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.
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Affiliation(s)
- Patricia Pais-Roldán
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine 1, Structural and Functional Organisation of the Brain, Forschungszentrum Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Heinrich-Heine-University, Düsseldorf, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and Medicine 11, Molecular Neuroscience and Neuroimaging, JARA, Forschungszentrum Jülich, Jülich, Germany
- JARA–BRAIN–Translational Medicine, Aachen, Germany
- Department of Neurology, RWTH Aachen University, Aachen, Germany
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32
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Li C, Hu J, Xing Y, Han J, Zhang A, Zhang Y, Hua Y, Tian Z, Bai Y. Constraint-induced movement therapy alleviates motor impairment by inhibiting the accumulation of neutrophil extracellular traps in ischemic cortex. Neurobiol Dis 2023; 179:106064. [PMID: 36878327 DOI: 10.1016/j.nbd.2023.106064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 02/25/2023] [Accepted: 03/01/2023] [Indexed: 03/07/2023] Open
Abstract
Stroke is a major cause of mortality and morbidity and most acute strokes are ischemic. Evidence-based medicine has demonstrated the effectiveness of constraint-induced movement therapy (CIMT) in the recovery of motor function in patients after ischemic stroke, but the specific treatment mechanism remains unclear. Herein, our integrated transcriptomics and multiple enrichment analysis studies, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) studies show that CIMT conduction broadly curtails immune response, neutrophil chemotaxis, and chemokine-mediated signaling pathway, CCR chemokine receptor binding. Those suggest the potential effect of CIMT on neutrophils in ischemic mice brain parenchyma. Recent studies have found that accumulating granulocytes release extracellular web-like structures composed of DNA and proteins called neutrophil extracellular traps (NETs), which destruct neurological function primarily by disrupting the blood-brain barrier and promoting thrombosis. However, the temporal and spatial distribution of neutrophils and their released NETs in parenchyma and their damaging effects on nerve cells remain unclear. Thus, utilizing immunofluorescence and flow cytometry, our analyses uncovered that NETs erode multiple regions such as primary motor cortex (M1), striatum (Str), nucleus of the vertical limb of the diagonal band (VDB), nucleus of the horizontal limb of the diagonal band (HDB) and medial septal nucleus (MS), and persist in the brain parenchyma for at least 14 days, while CIMT can reduce the content of NETs and chemokines CCL2 and CCL5 in M1. Intriguingly, CIMT failed to further reduce neurological deficits after inhibiting the NET formation by pharmacologic inhibition of peptidylarginine deiminase 4 (PAD4). Collectively, these results demonstrate that CIMT could alleviate cerebral ischemic injury induced locomotor deficits by modulating the activation of neutrophils. These data are expected to provide direct evidence for the expression of NETs in ischemic brain parenchyma and novel insights into the mechanisms of CIMT protecting against ischemic brain injury.
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Affiliation(s)
- Congqin Li
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jian Hu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Ying Xing
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jing Han
- State Key Laboratory of Medical Neurobiology, Department of Integrative Medicine and Neurobiology, Brain Science Collaborative Innovation Center, School of Basic Medical Sciences, Institutes of Brain Science, Fudan Institutes of Integrative Medicine, Fudan University, Shanghai, China
| | - Anjing Zhang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuqian Zhang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yan Hua
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhanzhuang Tian
- State Key Laboratory of Medical Neurobiology, Department of Integrative Medicine and Neurobiology, Brain Science Collaborative Innovation Center, School of Basic Medical Sciences, Institutes of Brain Science, Fudan Institutes of Integrative Medicine, Fudan University, Shanghai, China
| | - Yulong Bai
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
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33
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Schellekens W, Bhogal AA, Roefs ECA, Báez-Yáñez MG, Siero JCW, Petridou N. The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth. J Cereb Blood Flow Metab 2023; 43:419-432. [PMID: 36262088 PMCID: PMC9941862 DOI: 10.1177/0271678x221133972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 09/01/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022]
Abstract
Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.
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Affiliation(s)
- Wouter Schellekens
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Alex A Bhogal
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Emiel CA Roefs
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Mario G Báez-Yáñez
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Jeroen CW Siero
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
- Spinoza Centre for Neuroimaging, Amsterdam, The
Netherlands
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
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34
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Zachlod D, Palomero-Gallagher N, Dickscheid T, Amunts K. Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity. Biol Psychiatry 2023; 93:471-479. [PMID: 36567226 DOI: 10.1016/j.biopsych.2022.09.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/18/2022] [Accepted: 09/10/2022] [Indexed: 02/04/2023]
Abstract
This review focuses on cytoarchitectonics and receptor architectonics as biological correlates of function and connectivity. It introduces the 3-dimensional cytoarchitectonic probabilistic maps of cortical areas and nuclei of the Julich-Brain Atlas, available at EBRAINS, to study structure-function relationships. The maps are linked to the BigBrain as microanatomical reference model and template space. The siibra software tool suite enables programmatic access to the maps and to receptor architectonic data that are anchored to brain areas. Such cellular and molecular data are tools for studying magnetic resonance connectivity including modeling and simulation. At the end, we highlight perspectives of the Julich-Brain as well as methodological considerations. Thus, microstructural maps as part of a multimodal atlas help elucidate the biological correlates of large-scale networks and brain function with a high level of anatomical detail, which provides a basis to study brains of patients with psychiatric disorders.
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Affiliation(s)
- Daniel Zachlod
- Institute of Neurosciences and Medicine, Research Centre Jülich, Jülich, Germany.
| | - Nicola Palomero-Gallagher
- Institute of Neurosciences and Medicine, Research Centre Jülich, Jülich, Germany; C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Department of Psychiatry, Psychotherapy, Psychosomatics, Medical Faculty, RWTH Aachen, Jülich Aachen Research Alliance-Translational Brain Medicine, Aachen, Germany
| | - Timo Dickscheid
- Institute of Neurosciences and Medicine, Research Centre Jülich, Jülich, Germany; Helmholtz AI, Research Centre Jülich, Jülich, Germany; Department of Computer Science, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Katrin Amunts
- Institute of Neurosciences and Medicine, Research Centre Jülich, Jülich, Germany; C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
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35
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High-resolution magnetization-transfer imaging of post-mortem marmoset brain: Comparisons with relaxometry and histology. Neuroimage 2023; 268:119860. [PMID: 36610679 DOI: 10.1016/j.neuroimage.2023.119860] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/28/2022] [Accepted: 01/03/2023] [Indexed: 01/07/2023] Open
Abstract
Cell membranes and macromolecules or paramagnetic compounds interact with water proton spins, which modulates magnetic resonance imaging (MRI) contrast providing information on tissue composition. For a further investigation, quantitative magnetization transfer (qMT) parameters (at 3T), including the ratio of the macromolecular and water proton pools, F, and the exchange-rate constant as well as the (observed) longitudinal and the effective transverse relaxation rates (at 3T and 7T), R1obs and R2*, respectively, were measured at high spatial resolution (200 µm) in a slice of fixed marmoset brain and compared to histology results obtained with Gallyas' myelin stain and Perls' iron stain. R1obs and R2* were linearly correlated with the iron content for the entire slice, whereas distinct differences were obtained between gray and white matter for correlations of relaxometry and qMT parameters with myelin content. The combined results suggest that the macromolecular pool interacting with water consists of myelin and (less efficient) non-myelin contributions. Despite strong correlation of F and R1obs, none of these parameters was uniquely specific to myelination. Due to additional sensitivity to iron stores, R1obs and R2* were more sensitive for depicting microstructural differences between cortical layers than F.
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36
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Rollenhagen A, Anstötz M, Zimmermann K, Kasugai Y, Sätzler K, Molnar E, Ferraguti F, Lübke JHR. Layer-specific distribution and expression pattern of AMPA- and NMDA-type glutamate receptors in the barrel field of the adult rat somatosensory cortex: a quantitative electron microscopic analysis. Cereb Cortex 2023; 33:2342-2360. [PMID: 35732315 PMCID: PMC9977369 DOI: 10.1093/cercor/bhac212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/14/2022] Open
Abstract
AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) and NMDA (N-methyl-d-aspartate) glutamate receptors are driving forces for synaptic transmission and plasticity at neocortical synapses. However, their distribution pattern in the adult rat neocortex is largely unknown and was quantified using freeze fracture replication combined with postimmunogold-labeling. Both receptors were co-localized at layer (L)4 and L5 postsynaptic densities (PSDs). At L4 dendritic shaft and spine PSDs, the number of gold grains detecting AMPA was similar, whereas at L5 shaft PSDs AMPA-receptors outnumbered those on spine PSDs. Their number was significantly higher at L5 vs. L4 PSDs. At L4 and L5 dendritic shaft PSDs, the number of gold grains detecting GluN1 was ~2-fold higher than at spine PSDs. The number of gold grains detecting the GluN1-subunit was higher for both shaft and spine PSDs in L5 vs. L4. Both receptors showed a large variability in L4 and L5. A high correlation between the number of gold grains and PSD size for both receptors and targets was observed. Both receptors were distributed over the entire PSD but showed a layer- and target-specific distribution pattern. The layer- and target-specific distribution of AMPA and GluN1 glutamate receptors partially contribute to the observed functional differences in synaptic transmission and plasticity in the neocortex.
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Affiliation(s)
- Astrid Rollenhagen
- Institute of Neuroscience and Medicine INM-10, Research Centre Jülich GmbH, Leo Brandt Str., Jülich 52425, Germany
| | - Max Anstötz
- Institute of Neuroscience and Medicine INM-10, Research Centre Jülich GmbH, Leo Brandt Str., Jülich 52425, Germany.,Institute of Anatomy II, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Universitätsstr. 1, Düsseldorf 40001, Germany
| | - Kerstin Zimmermann
- Institute of Neuroscience and Medicine INM-10, Research Centre Jülich GmbH, Leo Brandt Str., Jülich 52425, Germany
| | - Yu Kasugai
- Department of Pharmacology, Medical University of Innsbruck, Peter Mayr Strasse 1a, Innsbruck A-6020, Austria
| | - Kurt Sätzler
- School of Biomedical Sciences, University of Ulster, Cromore Rd., Londonderry BT52 1SA, United Kingdom
| | - Elek Molnar
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, University Walk, Bristol BS8 1TD, United Kingdom
| | - Francesco Ferraguti
- Department of Pharmacology, Medical University of Innsbruck, Peter Mayr Strasse 1a, Innsbruck A-6020, Austria
| | - Joachim H R Lübke
- Institute of Neuroscience and Medicine INM-10, Research Centre Jülich GmbH, Leo Brandt Str., Jülich 52425, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH/Medical University Aachen, Pauwelstr. 30, Aachen 52074, Germany.,JARA Translational Medicine Jülich/Aachen, Germany
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37
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Zong F, Min X, Zhang Y, Li Y, Zhang X, Liu Y, He K. Circadian time- and sleep-dependent modulation of cortical parvalbumin-positive inhibitory neurons. EMBO J 2023; 42:e111304. [PMID: 36477886 PMCID: PMC9890233 DOI: 10.15252/embj.2022111304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 10/13/2022] [Accepted: 11/04/2022] [Indexed: 12/12/2022] Open
Abstract
Parvalbumin-positive neurons (PVs) are the main class of inhibitory neurons in the mammalian central nervous system. By examining diurnal changes in synaptic and neuronal activity of PVs in the supragranular layer of the mouse primary visual cortex (V1), we found that both PV input and output are modulated in a time- and sleep-dependent manner throughout the 24-h day. We first show that PV-evoked inhibition is stronger by the end of the light cycle (ZT12) relative to the end of the dark cycle (ZT0), which is in line with the lower inhibitory input of PV neurons at ZT12 than at ZT0. Interestingly, PV inhibitory and excitatory synaptic transmission slowly oscillate in opposite directions during the light/dark cycle. Although excitatory synapses are predominantly regulated by experience, inhibitory synapses are regulated by sleep, via acetylcholine activating M1 receptors. Consistent with synaptic regulation of PVs, we further show in vivo that spontaneous PV activity displays daily rhythm mainly determined by visual experience, which negatively correlates with the activity cycle of surrounding pyramidal neurons and the dorsal lateral geniculate nucleus-evoked responses in V1. These findings underscore the physiological significance of PV's daily modulation.
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Affiliation(s)
- Fang‐Jiao Zong
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- Present address:
Qingdao University School of PharmacyQingdaoChina
| | - Xia Min
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yan Zhang
- Shanghai Open UniversityShanghaiChina
| | - Yu‐Ke Li
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Xue‐Ting Zhang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yang Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Kai‐Wen He
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
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38
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Renner J, Rasia-Filho AA. Morphological Features of Human Dendritic Spines. ADVANCES IN NEUROBIOLOGY 2023; 34:367-496. [PMID: 37962801 DOI: 10.1007/978-3-031-36159-3_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Dendritic spine features in human neurons follow the up-to-date knowledge presented in the previous chapters of this book. Human dendrites are notable for their heterogeneity in branching patterns and spatial distribution. These data relate to circuits and specialized functions. Spines enhance neuronal connectivity, modulate and integrate synaptic inputs, and provide additional plastic functions to microcircuits and large-scale networks. Spines present a continuum of shapes and sizes, whose number and distribution along the dendritic length are diverse in neurons and different areas. Indeed, human neurons vary from aspiny or "relatively aspiny" cells to neurons covered with a high density of intermingled pleomorphic spines on very long dendrites. In this chapter, we discuss the phylogenetic and ontogenetic development of human spines and describe the heterogeneous features of human spiny neurons along the spinal cord, brainstem, cerebellum, thalamus, basal ganglia, amygdala, hippocampal regions, and neocortical areas. Three-dimensional reconstructions of Golgi-impregnated dendritic spines and data from fluorescence microscopy are reviewed with ultrastructural findings to address the complex possibilities for synaptic processing and integration in humans. Pathological changes are also presented, for example, in Alzheimer's disease and schizophrenia. Basic morphological data can be linked to current techniques, and perspectives in this research field include the characterization of spines in human neurons with specific transcriptome features, molecular classification of cellular diversity, and electrophysiological identification of coexisting subpopulations of cells. These data would enlighten how cellular attributes determine neuron type-specific connectivity and brain wiring for our diverse aptitudes and behavior.
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Affiliation(s)
- Josué Renner
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
| | - Alberto A Rasia-Filho
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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39
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Ni HC, Chao YP, Tseng RY, Wu CT, Cocchi L, Chou TL, Chen RS, Gau SSF, Yeh CH, Lin HY. Lack of effects of four-week theta burst stimulation on white matter macro/microstructure in children and adolescents with autism. Neuroimage Clin 2023; 37:103324. [PMID: 36638598 PMCID: PMC9852693 DOI: 10.1016/j.nicl.2023.103324] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 12/18/2022] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
Following the published behavioral and cognitive results of this single-blind parallel sham-controlled randomized clinical trial, the current study aimed to explore the impact of intermittent theta burst stimulation (iTBS), a variant of excitatory transcranial magnetic stimulation, over the bilateral posterior superior temporal sulci (pSTS) on white matter macro/microstructure in intellectually able children and adolescents with autism. Participants were randomized and blindly received active or sham iTBS for 4 weeks (the single-blind sham-controlled phase). Then, all participants continued to receive active iTBS for another 4 weeks (the open-label phase). The clinical results were published elsewhere. Here, we present diffusion magnetic resonance imaging data on potential changes in white matter measures after iTBS. Twenty-two participants in Active-Active group and 27 participants in Sham-Active group underwent multi-shell high angular resolution diffusion imaging (64-direction for b = 2000 & 1000 s/mm2, respectively) at baseline, week 4, and week 8. With longitudinal fixel-based analysis, we found no white matter changes following iTBS from baseline to week 4 (a null treatment by time interaction and a null within-group paired comparison in the Active-Active group), nor from baseline to week 8 (null within-group paired comparisons in both Active-Active and Sham-Active groups). As for the brain-symptoms relationship, we did not find baseline white matter metrics associated with symptom changes at week 4 in either group. Our results raise the question of what the minimal cumulative stimulation dose required to induce the white matter plasticity is.
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Affiliation(s)
- Hsing-Chang Ni
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Yi-Ping Chao
- Deparment of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan; Department of Otorhinolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Rung-Yu Tseng
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan
| | - Chen-Te Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Luca Cocchi
- Clinical Brain Networks Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tai-Li Chou
- Department of Psychology, National Taiwan University, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
| | - Rou-Shayn Chen
- Department of Neurology, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Susan Shur-Fen Gau
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Chun-Hung Yeh
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan.
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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40
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Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain. Neuroimage 2022; 264:119671. [PMID: 36209794 DOI: 10.1016/j.neuroimage.2022.119671] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/29/2022] [Accepted: 10/05/2022] [Indexed: 11/07/2022] Open
Abstract
Neurotransmitter receptors modulate signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression measuring mRNA transcripts is often used as a proxy for receptor densities. In the present report, we comprehensively test the spatial correlation between gene expression and protein density for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography radioligand-based imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT1A, CB1, D2, and MOR). These expression-density associations are related to gene differential stability and can vary between cortical and subcortical structures. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function.
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41
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Hansen JY, Shafiei G, Markello RD, Smart K, Cox SML, Nørgaard M, Beliveau V, Wu Y, Gallezot JD, Aumont É, Servaes S, Scala SG, DuBois JM, Wainstein G, Bezgin G, Funck T, Schmitz TW, Spreng RN, Galovic M, Koepp MJ, Duncan JS, Coles JP, Fryer TD, Aigbirhio FI, McGinnity CJ, Hammers A, Soucy JP, Baillet S, Guimond S, Hietala J, Bedard MA, Leyton M, Kobayashi E, Rosa-Neto P, Ganz M, Knudsen GM, Palomero-Gallagher N, Shine JM, Carson RE, Tuominen L, Dagher A, Misic B. Mapping neurotransmitter systems to the structural and functional organization of the human neocortex. Nat Neurosci 2022; 25:1569-1581. [PMID: 36303070 PMCID: PMC9630096 DOI: 10.1038/s41593-022-01186-3] [Citation(s) in RCA: 164] [Impact Index Per Article: 82.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 09/20/2022] [Indexed: 01/13/2023]
Abstract
Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.
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Affiliation(s)
- Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Golia Shafiei
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Ross D Markello
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Kelly Smart
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Sylvia M L Cox
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Martin Nørgaard
- Department of Psychology, Center for Reproducible Neuroscience, Stanford University, Stanford, CA, USA
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Vincent Beliveau
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Yanjun Wu
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Jean-Dominique Gallezot
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Étienne Aumont
- Cognitive Pharmacology Research Unit, UQAM, Montréal, QC, Canada
| | - Stijn Servaes
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | | | | | | | - Gleb Bezgin
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | - Thomas Funck
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Taylor W Schmitz
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - R Nathan Spreng
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Jonathan P Coles
- Department of Medicine, Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Tim D Fryer
- Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Colm J McGinnity
- King's College London and Guy's and St. Thomas' PET Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Alexander Hammers
- King's College London and Guy's and St. Thomas' PET Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Jean-Paul Soucy
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Sylvain Baillet
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Synthia Guimond
- Department of Psychiatry, Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Psychoeducation and Psychology, University of Quebec in Outaouais, Gatineau, QC, Canada
| | - Jarmo Hietala
- Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Marc-André Bedard
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Cognitive Pharmacology Research Unit, UQAM, Montréal, QC, Canada
| | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Eliane Kobayashi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Pedro Rosa-Neto
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | - Melanie Ganz
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - James M Shine
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Richard E Carson
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lauri Tuominen
- Department of Psychiatry, Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Alain Dagher
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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42
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Karahan E, Tait L, Si R, Özkan A, Szul MJ, Graham KS, Lawrence AD, Zhang J. The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure. Commun Biol 2022; 5:1007. [PMID: 36151363 PMCID: PMC9508245 DOI: 10.1038/s42003-022-03974-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 09/09/2022] [Indexed: 11/09/2022] Open
Abstract
Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV.
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Affiliation(s)
- Esin Karahan
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Luke Tait
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
| | - Ruoguang Si
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Ayşegül Özkan
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Maciek J Szul
- Institut des Sciences Cognitives Marc Jeannerod, CNRS UMR 5229, Bron, France.,Université Claude Bernard Lyon I, Lyon, France
| | - Kim S Graham
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew D Lawrence
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Jiaxiang Zhang
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom. .,Department of Computer Science, Swansea University, Swansea, United Kingdom.
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43
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Wei L, Ding M, Zhang Y, Wang H. Decoding transcriptional signatures of the association between free water and macroscale organizations in healthy adolescents. Neuroimage 2022; 261:119514. [PMID: 35901916 DOI: 10.1016/j.neuroimage.2022.119514] [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: 01/04/2022] [Revised: 07/11/2022] [Accepted: 07/22/2022] [Indexed: 11/16/2022] Open
Abstract
We leveraged a novel index of diffusion MRI to investigate the relationships among cortical free water, macro-organizations and gene expression in healthy adults. Few research has been conducted to investigate the role of free water in the healthy adults due to it can easily be affected also by aging diseases. High quality data of 350 subjects from Human Connectome Project were used in our study. Cortical free water was estimated by using a bi-tensor model. The free water was high in the limbic, insular and somatosensory cortex, while being lower in motor and association cortex. The negative correlation between the free water and cortical thickness has been consistently identified in almost all the cortical regions. Negative correlation between the cortical free water and structural covariance (rho=-0.38, pspin=0.005) revealed the free water was sensitive to cortical heterogeneity. Using human gene expression dataset, we found the gene expression pattern of the relationship between the free water and cortical thickness spatially coupled with primary gradient of structural covariance network (rho=0.40, pspin=0.004). Our findings indicated the free water was sensitive to the cortical cellular status. The relationship between free water and macroscale organization also reflected hierarchal structures of cerebral cortex.
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Affiliation(s)
- Lei Wei
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
| | - Ming Ding
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - Yuwen Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China; Human Phenome Institute, Fudan University, Shanghai, PR China; Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, PR China.
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44
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In-vivo data-driven parcellation of Heschl's gyrus using structural connectivity. Sci Rep 2022; 12:11292. [PMID: 35788143 PMCID: PMC9253310 DOI: 10.1038/s41598-022-15083-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 06/17/2022] [Indexed: 12/05/2022] Open
Abstract
The human auditory cortex around Heschl’s gyrus (HG) exhibits diverging patterns across individuals owing to the heterogeneity of its substructures. In this study, we investigated the subregions of the human auditory cortex using data-driven machine-learning techniques at the individual level and assessed their structural and functional profiles. We studied an openly accessible large dataset of the Human Connectome Project and identified the subregions of the HG in humans using data-driven clustering techniques with individually calculated imaging features of cortical folding and structural connectivity information obtained via diffusion magnetic resonance imaging tractography. We characterized the structural and functional profiles of each HG subregion according to the cortical morphology, microstructure, and functional connectivity at rest. We found three subregions. The first subregion (HG1) occupied the central portion of HG, the second subregion (HG2) occupied the medial-posterior-superior part of HG, and the third subregion (HG3) occupied the lateral-anterior-inferior part of HG. The HG3 exhibited strong structural and functional connectivity to the association and paralimbic areas, and the HG1 exhibited a higher myelin density and larger cortical thickness than other subregions. A functional gradient analysis revealed a gradual axis expanding from the HG2 to the HG3. Our findings clarify the individually varying structural and functional organization of human HG subregions and provide insights into the substructures of the human auditory cortex.
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45
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Katsumi Y, Wong B, Cavallari M, Fong TG, Alsop DC, Andreano JM, Carvalho N, Brickhouse M, Jones R, Libermann TA, Marcantonio ER, Schmitt E, Shafi MM, Pascual-Leone A, Travison T, Barrett LF, Inouye SK, Dickerson BC, Touroutoglou A. Structural integrity of the anterior mid-cingulate cortex contributes to resilience to delirium in SuperAging. Brain Commun 2022; 4:fcac163. [PMID: 35822100 PMCID: PMC9272062 DOI: 10.1093/braincomms/fcac163] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 05/24/2022] [Accepted: 06/20/2022] [Indexed: 12/12/2022] Open
Abstract
Despite its devastating clinical and societal impact, approaches to treat delirium in older adults remain elusive, making it important to identify factors that may confer resilience to this syndrome. Here, we investigated a cohort of 93 cognitively normal older patients undergoing elective surgery recruited as part of the Successful Aging after Elective Surgery study. Each participant was classified either as a SuperAger (n = 19) or typically aging older adult (n = 74) based on neuropsychological criteria, where the former was defined as those older adults whose memory function rivals that of young adults. We compared these subgroups to examine the role of preoperative memory function in the incidence and severity of postoperative delirium. We additionally investigated the association between indices of postoperative delirium symptoms and cortical thickness in functional networks implicated in SuperAging based on structural magnetic resonance imaging data that were collected preoperatively. We found that SuperAging confers the real-world benefit of resilience to delirium, as shown by lower (i.e. zero) incidence of postoperative delirium and decreased severity scores compared with typical older adults. Furthermore, greater baseline cortical thickness of the anterior mid-cingulate cortex-a key node of the brain's salience network that is also consistently implicated in SuperAging-predicted lower postoperative delirium severity scores in all patients. Taken together, these findings suggest that baseline memory function in older adults may be a useful predictor of postoperative delirium risk and severity and that superior memory function may contribute to resilience to delirium. In particular, the integrity of the anterior mid-cingulate cortex may be a potential biomarker of resilience to delirium, pointing to this region as a potential target for preventive or therapeutic interventions designed to mitigate the risk or consequences of developing this prevalent clinical syndrome.
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Affiliation(s)
- Yuta Katsumi
- Harvard Medical School, Boston MA, USA
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston MA, USA
| | - Bonnie Wong
- Harvard Medical School, Boston MA, USA
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston MA, USA
| | - Michele Cavallari
- Harvard Medical School, Boston MA, USA
- Center for Neurologlical Imaging, Department of Radiology, Brigham and Women’s Hospital, Boston MA, USA
| | - Tamara G Fong
- Harvard Medical School, Boston MA, USA
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston MA, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - David C Alsop
- Harvard Medical School, Boston MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - Joseph M Andreano
- Harvard Medical School, Boston MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston MA, USA
| | - Nicole Carvalho
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston MA, USA
| | - Michael Brickhouse
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston MA, USA
| | - Richard Jones
- Department of Psychiatry and Human Behavior and Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Towia A Libermann
- Harvard Medical School, Boston MA, USA
- Genomics, Proteomics, Bioinformatics and Systems Biology Center, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - Edward R Marcantonio
- Harvard Medical School, Boston MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - Eva Schmitt
- Harvard Medical School, Boston MA, USA
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston MA, USA
| | - Mouhsin M Shafi
- Harvard Medical School, Boston MA, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston MA, USA
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - Alvaro Pascual-Leone
- Harvard Medical School, Boston MA, USA
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - Thomas Travison
- Harvard Medical School, Boston MA, USA
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston MA, USA
| | - Lisa Feldman Barrett
- Harvard Medical School, Boston MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston MA, USA
- Department of Psychology, Northeastern University, Boston MA, USA
| | - Sharon K Inouye
- Harvard Medical School, Boston MA, USA
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston MA, USA
| | - Bradford C Dickerson
- Harvard Medical School, Boston MA, USA
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston MA, USA
- Massachusetts Alzheimer’s Disease Research Center, Massachusetts General Hospital, Boston MA, USA
| | - Alexandra Touroutoglou
- Harvard Medical School, Boston MA, USA
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Boston MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston MA, USA
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46
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Fernandez-Alvarez M, Atienza M, Zallo F, Matute C, Capetillo-Zarate E, Cantero JL. Linking Plasma Amyloid Beta and Neurofilament Light Chain to Intracortical Myelin Content in Cognitively Normal Older Adults. Front Aging Neurosci 2022; 14:896848. [PMID: 35783126 PMCID: PMC9247578 DOI: 10.3389/fnagi.2022.896848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022] Open
Abstract
Evidence suggests that lightly myelinated cortical regions are vulnerable to aging and Alzheimer’s disease (AD). However, it remains unknown whether plasma markers of amyloid and neurodegeneration are related to deficits in intracortical myelin content, and whether this relationship, in turn, is associated with altered patterns of resting-state functional connectivity (rs-FC). To shed light into these questions, plasma levels of amyloid-β fragment 1–42 (Aβ1–42) and neurofilament light chain (NfL) were measured using ultra-sensitive single-molecule array (Simoa) assays, and the intracortical myelin content was estimated with the ratio T1-weigthed/T2-weighted (T1w/T2w) in 133 cognitively normal older adults. We assessed: (i) whether plasma Aβ1–42 and/or NfL levels were associated with intracortical myelin content at different cortical depths and (ii) whether cortical regions showing myelin reductions also exhibited altered rs-FC patterns. Surface-based multiple regression analyses revealed that lower plasma Aβ1–42 and higher plasma NfL were associated with lower myelin content in temporo-parietal-occipital regions and the insular cortex, respectively. Whereas the association with Aβ1–42 decreased with depth, the NfL-myelin relationship was most evident in the innermost layer. Older individuals with higher plasma NfL levels also exhibited altered rs-FC between the insula and medial orbitofrontal cortex. Together, these findings establish a link between plasma markers of amyloid/neurodegeneration and intracortical myelin content in cognitively normal older adults, and support the role of plasma NfL in boosting aberrant FC patterns of the insular cortex, a central brain hub highly vulnerable to aging and neurodegeneration.
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Affiliation(s)
- Marina Fernandez-Alvarez
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Fatima Zallo
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Carlos Matute
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Estibaliz Capetillo-Zarate
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Jose L. Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- *Correspondence: Jose L. Cantero,
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47
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Park BY, Larivière S, Rodríguez-Cruces R, Royer J, Tavakol S, Wang Y, Caciagli L, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Alvim MKM, Yasuda C, Bonilha L, Gleichgerrcht E, Focke NK, Kreilkamp BAK, Domin M, von Podewils F, Langner S, Rummel C, Rebsamen M, Wiest R, Martin P, Kotikalapudi R, Bender B, O’Brien TJ, Law M, Sinclair B, Vivash L, Kwan P, Desmond PM, Malpas CB, Lui E, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Lenge M, Guerrini R, Bartolini E, Hamandi K, Foley S, Weber B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Severino M, Striano P, Parodi C, Tortora D, Hatton SN, Vos SB, Duncan JS, Galovic M, Whelan CD, Bargalló N, Pariente J, Conde-Blanco E, Vaudano AE, Tondelli M, Meletti S, Kong X, Francks C, Fisher SE, Caldairou B, Ryten M, Labate A, Sisodiya SM, Thompson PM, McDonald CR, Bernasconi A, Bernasconi N, Bernhardt BC. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy. Brain 2022; 145:1285-1298. [PMID: 35333312 PMCID: PMC9128824 DOI: 10.1093/brain/awab417] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 07/15/2021] [Accepted: 08/14/2021] [Indexed: 12/20/2022] Open
Abstract
Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.
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Affiliation(s)
- Bo-yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Data Science, Inha University, Incheon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raul Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Yezhou Wang
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Fernando Cendes
- Department of Neurology, University of Campinas–UNICAMP, Campinas, São Paulo, Brazil
| | - Marina K M Alvim
- Department of Neurology, University of Campinas–UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas–UNICAMP, Campinas, São Paulo, Brazil
| | | | | | - Niels K Focke
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | | | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewils
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Michael Rebsamen
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Benjamin Bender
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Terence J O’Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patricia M Desmond
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Charles B Malpas
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Elaine Lui
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Colin P Doherty
- Department of Neurology, St James’ Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, Member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Rhys H Thomas
- Transitional and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Department of Artificial Intelligence, Xiamen University, Xiamen, China
| | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Children’s Hospital A. Meyer-University of Florence, Florence, Italy
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children’s Hospital A. Meyer-University of Florence, Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Children’s Hospital A. Meyer-University of Florence, Florence, Italy
| | - Emanuele Bartolini
- USL Centro Toscana, Neurology Unit, Nuovo Ospedale Santo Stefano, Prato, Italy
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J A Carr
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Eugenio Abela
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Mark P Richardson
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariasavina Severino
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Costanza Parodi
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Domenico Tortora
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Sean N Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| | - Marian Galovic
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Christopher D Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Núria Bargalló
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Radiology CDIC, Hospital Clinic Barcelona, Barcelona, Spain
| | - Jose Pariente
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Xiang‐Zhen Kong
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Mina Ryten
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Angelo Labate
- Neurology, BIOMORF Department, University of Messina, Messina, Italy
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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48
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Tian D, Izumi SI. Transcranial Magnetic Stimulation and Neocortical Neurons: The Micro-Macro Connection. Front Neurosci 2022; 16:866245. [PMID: 35495053 PMCID: PMC9039343 DOI: 10.3389/fnins.2022.866245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/28/2022] [Indexed: 12/20/2022] Open
Abstract
Understanding the operation of cortical circuits is an important and necessary task in both neuroscience and neurorehabilitation. The functioning of the neocortex results from integrative neuronal activity, which can be probed non-invasively by transcranial magnetic stimulation (TMS). Despite a clear indication of the direct involvement of cortical neurons in TMS, no explicit connection model has been made between the microscopic neuronal landscape and the macroscopic TMS outcome. Here we have performed an integrative review of multidisciplinary evidence regarding motor cortex neurocytology and TMS-related neurophysiology with the aim of elucidating the micro–macro connections underlying TMS. Neurocytological evidence from animal and human studies has been reviewed to describe the landscape of the cortical neurons covering the taxonomy, morphology, circuit wiring, and excitatory–inhibitory balance. Evidence from TMS studies in healthy humans is discussed, with emphasis on the TMS pulse and paradigm selectivity that reflect the underlying neural circuitry constitution. As a result, we propose a preliminary neuronal model of the human motor cortex and then link the TMS mechanisms with the neuronal model by stimulus intensity, direction of induced current, and paired-pulse timing. As TMS bears great developmental potential for both a probe and modulator of neural network activity and neurotransmission, the connection model will act as a foundation for future combined studies of neurocytology and neurophysiology, as well as the technical advances and application of TMS.
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Affiliation(s)
- Dongting Tian
- Department of Physical Medicine and Rehabilitation, Tohoku University Graduates School of Medicine, Sendai, Japan
- *Correspondence: Dongting Tian,
| | - Shin-Ichi Izumi
- Department of Physical Medicine and Rehabilitation, Tohoku University Graduates School of Medicine, Sendai, Japan
- Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan
- Shin-Ichi Izumi,
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49
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Amunts K, DeFelipe J, Pennartz C, Destexhe A, Migliore M, Ryvlin P, Furber S, Knoll A, Bitsch L, Bjaalie JG, Ioannidis Y, Lippert T, Sanchez-Vives MV, Goebel R, Jirsa V. Linking Brain Structure, Activity, and Cognitive Function through Computation. eNeuro 2022; 9:ENEURO.0316-21.2022. [PMID: 35217544 PMCID: PMC8925650 DOI: 10.1523/eneuro.0316-21.2022] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 01/11/2022] [Accepted: 01/17/2022] [Indexed: 01/19/2023] Open
Abstract
Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.
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Affiliation(s)
- Katrin Amunts
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich 52425, Germany
- C. & O. Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf 40225, Germany
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Madrid 28002, Spain
| | - Cyriel Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, 1098 XH, The Netherlands
| | - Alain Destexhe
- Centre National de la Recherche Scientifique, Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Gif sur Yvette 91400, France
| | - Michele Migliore
- Institute of Biophysics, National Research Council, Palermo 90146, Italy
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne CH-1011, Switzerland
| | - Steve Furber
- Department of Computer Science, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Alois Knoll
- Department of Informatics, Technical University of Munich, Garching 385748, Germany
| | - Lise Bitsch
- The Danish Board of Technology Foundation, Copenhagen, 2650 Hvidovre, Denmark
| | - Jan G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Yannis Ioannidis
- ATHENA Research & Innovation Center, Athena 12125, Greece
- Department of Informatics & Telecom, Nat'l and Kapodistrian University of Athens, 157 84 Athens, Greece
| | - Thomas Lippert
- Institute for Advanced Simulation (IAS), Jülich Supercomputing Centre (JSC), Research Centre Jülich, Jülich 52425, Germany
| | - Maria V Sanchez-Vives
- ICREA and Systems Neuroscience, Institute of Biomedical Investigations August Pi i Sunyer, Barcelona 08036, Spain
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6229 EV, The Netherlands
| | - Viktor Jirsa
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106, Marseille 13005, France
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Rasia-Filho AA. Unraveling Brain Microcircuits, Dendritic Spines, and Synaptic Processing Using Multiple Complementary Approaches. Front Physiol 2022; 13:831568. [PMID: 35295578 PMCID: PMC8918670 DOI: 10.3389/fphys.2022.831568] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/26/2022] [Indexed: 12/21/2022] Open
Affiliation(s)
- Alberto A. Rasia-Filho
- Department of Basic Sciences/Physiology, Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
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