1
|
Damera SR, De Asis-Cruz J, Cook KM, Kapse K, Spoehr E, Murnick J, Basu S, Andescavage N, Limperopoulos C. Regional homogeneity as a marker of sensory cortex dysmaturity in preterm infants. iScience 2024; 27:109662. [PMID: 38665205 PMCID: PMC11043889 DOI: 10.1016/j.isci.2024.109662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/23/2024] [Accepted: 04/01/2024] [Indexed: 04/28/2024] Open
Abstract
Atypical perinatal sensory experience in preterm infants is thought to increase their risk of neurodevelopmental disabilities by altering the development of the sensory cortices. Here, we used resting-state fMRI data from preterm and term-born infants scanned between 32 and 48 weeks post-menstrual age to assess the effect of early ex-utero exposure on sensory cortex development. Specifically, we utilized a measure of local correlated-ness called regional homogeneity (ReHo). First, we demonstrated that the brain-wide distribution of ReHo mirrors the known gradient of cortical maturation. Next, we showed that preterm birth differentially reduces ReHo across the primary sensory cortices. Finally, exploratory analyses showed that the reduction of ReHo in the primary auditory cortex of preterm infants is related to increased risk of autism at 18 months. In sum, we show that local connectivity within sensory cortices has different developmental trajectories, is differentially affected by preterm birth, and may be associated with later neurodevelopment.
Collapse
Affiliation(s)
- Srikanth R. Damera
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kevin M. Cook
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kushal Kapse
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Emma Spoehr
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Jon Murnick
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Sudeepta Basu
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Nickie Andescavage
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| |
Collapse
|
2
|
Liu J, Chen H, Cornea E, Gilmore JH, Gao W. Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy. Cereb Cortex 2023; 33:10367-10379. [PMID: 37585708 PMCID: PMC10545442 DOI: 10.1093/cercor/bhad288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 07/13/2023] [Indexed: 08/18/2023] Open
Abstract
Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.
Collapse
Affiliation(s)
- Janelle Liu
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
| | - Haitao Chen
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC 27514, United States
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC 27514, United States
| | - Wei Gao
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, United States
| |
Collapse
|
3
|
Nielsen AN, Kaplan S, Meyer D, Alexopoulos D, Kenley JK, Smyser TA, Wakschlag LS, Norton ES, Raghuraman N, Warner BB, Shimony JS, Luby JL, Neil JJ, Petersen SE, Barch DM, Rogers CE, Sylvester CM, Smyser CD. Maturation of large-scale brain systems over the first month of life. Cereb Cortex 2023; 33:2788-2803. [PMID: 35750056 PMCID: PMC10016041 DOI: 10.1093/cercor/bhac242] [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: 01/20/2022] [Revised: 04/29/2022] [Accepted: 05/23/2022] [Indexed: 01/14/2023] Open
Abstract
The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.
Collapse
Affiliation(s)
- Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dominique Meyer
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeanette K Kenley
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Tara A Smyser
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Lauren S Wakschlag
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Feinberg School of Medicine, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Elizabeth S Norton
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Nandini Raghuraman
- Department of Obstetrics and Gynecology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joshua S Shimony
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeffery J Neil
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Cynthia E Rogers
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| |
Collapse
|
4
|
Hanson KL, Weir RK, Iosif AM, Van de Water J, Carter CS, McAllister AK, Bauman MD, Schumann CM. Altered dendritic morphology in dorsolateral prefrontal cortex of nonhuman primates prenatally exposed to maternal immune activation. Brain Behav Immun 2023; 109:92-101. [PMID: 36610487 PMCID: PMC10023379 DOI: 10.1016/j.bbi.2023.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 12/06/2022] [Accepted: 01/03/2023] [Indexed: 01/06/2023] Open
Abstract
Women who contract a viral or bacterial infection during pregnancy have an increased risk of giving birth to a child with a neurodevelopmental or psychiatric disorder. The effects of maternal infection are likely mediated by the maternal immune response, as preclinical animal models have confirmed that maternal immune activation (MIA) leads to long lasting changes in offspring brain and behavior development. The present study sought to determine the impact of MIA-exposure during the first or second trimester on neuronal morphology in dorsolateral prefrontal cortex (DLPFC) and hippocampus from brain tissue obtained from MIA-exposed and control male rhesus monkey (Macaca mulatta) during late adolescence. MIA-exposed offspring display increased neuronal dendritic branching in pyramidal cells in DLPFC infra- and supragranular layers relative to controls, with no significant differences observed between offspring exposed to maternal infection in the first and second trimester. In addition, the diameter of apical dendrites in DLPFC infragranular layer is significantly decreased in MIA-exposed offspring relative to controls, irrespective of trimester exposure. In contrast, alterations in hippocampal neuronal morphology of MIA-exposed offspring were not evident. These findings demonstrate that a maternal immune challenge during pregnancy has long-term consequences for primate offspring dendritic structure, selectively in a brain region vital for socioemotional and cognitive development.
Collapse
Affiliation(s)
- Kari L Hanson
- Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, United States; MIND Institute, University of California, Davis, United States
| | - Ruth K Weir
- Innovation & Enterprise Department, University College London, United Kingdom
| | - Ana-Maria Iosif
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, United States
| | - Judy Van de Water
- MIND Institute, University of California, Davis, United States; Rheumatology/Allergy and Clinical Immunology, University of California, Davis, United States
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, United States; Center for Neuroscience, University of California, Davis, United States
| | | | - Melissa D Bauman
- Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, United States; MIND Institute, University of California, Davis, United States; California National Primate Research Center, University of California, Davis, United States.
| | - Cynthia M Schumann
- Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, United States; MIND Institute, University of California, Davis, United States.
| |
Collapse
|
5
|
Warhaftig G, Almeida D, Turecki G. Early life adversity across different cell- types in the brain. Neurosci Biobehav Rev 2023; 148:105113. [PMID: 36863603 DOI: 10.1016/j.neubiorev.2023.105113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/13/2023] [Accepted: 02/24/2023] [Indexed: 03/04/2023]
Abstract
Early life adversity (ELA)- which includes physical, psychological, emotional, and sexual abuse is one of the most common predictors to diverse psychopathologies later in adulthood. As ELA has a lasting impact on the brain at a developmental stage, recent findings from the field highlighted the specific contributions of different cell types to ELA and their association with long lasting consequences. In this review we will gather recent findings describing morphological, transcriptional and epigenetic alterations within neurons, glia and perineuronal nets and their associated cellular subpopulation. The findings reviewed and summarized here highlight important mechanisms underlying ELA and point to therapeutic approaches for ELA and related psychopathologies later in life.
Collapse
Affiliation(s)
- Gal Warhaftig
- McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal QC H4H 1R3, Canada
| | - Daniel Almeida
- McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal QC H4H 1R3, Canada
| | - Gustavo Turecki
- McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal QC H4H 1R3, Canada; Department of Psychiatry, McGill University, Montreal QC H3A 1A1, Canada.
| |
Collapse
|
6
|
Vanderhaeghen P, Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat Rev Neurosci 2023; 24:213-232. [PMID: 36792753 PMCID: PMC10064077 DOI: 10.1038/s41583-023-00675-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 02/17/2023]
Abstract
The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.
Collapse
Affiliation(s)
- Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium.
- Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Franck Polleux
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
| |
Collapse
|
7
|
Patel Y, Shin J, Abé C, Agartz I, Alloza C, Alnæs D, Ambrogi S, Antonucci LA, Arango C, Arolt V, Auzias G, Ayesa-Arriola R, Banaj N, Banaschewski T, Bandeira C, Başgöze Z, Cupertino RB, Bau CHD, Bauer J, Baumeister S, Bernardoni F, Bertolino A, Bonnin CDM, Brandeis D, Brem S, Bruggemann J, Bülow R, Bustillo JR, Calderoni S, Calvo R, Canales-Rodríguez EJ, Cannon DM, Carmona S, Carr VJ, Catts SV, Chenji S, Chew QH, Coghill D, Connolly CG, Conzelmann A, Craven AR, Crespo-Facorro B, Cullen K, Dahl A, Dannlowski U, Davey CG, Deruelle C, Díaz-Caneja CM, Dohm K, Ehrlich S, Epstein J, Erwin-Grabner T, Eyler LT, Fedor J, Fitzgerald J, Foran W, Ford JM, Fortea L, Fuentes-Claramonte P, Fullerton J, Furlong L, Gallagher L, Gao B, Gao S, Goikolea JM, Gotlib I, Goya-Maldonado R, Grabe HJ, Green M, Grevet EH, Groenewold NA, Grotegerd D, Gruber O, Haavik J, Hahn T, Harrison BJ, Heindel W, Henskens F, Heslenfeld DJ, Hilland E, Hoekstra PJ, Hohmann S, Holz N, Howells FM, Ipser JC, Jahanshad N, Jakobi B, Jansen A, Janssen J, Jonassen R, Kaiser A, Kaleda V, Karantonis J, King JA, Kircher T, Kochunov P, Koopowitz SM, Landén M, Landrø NI, Lawrie S, Lebedeva I, Luna B, Lundervold AJ, MacMaster FP, Maglanoc LA, Mathalon DH, McDonald C, McIntosh A, Meinert S, Michie PT, Mitchell P, Moreno-Alcázar A, Mowry B, Muratori F, Nabulsi L, Nenadić I, O'Gorman Tuura R, Oosterlaan J, Overs B, Pantelis C, Parellada M, Pariente JC, Pauli P, Pergola G, Piarulli FM, Picon F, Piras F, Pomarol-Clotet E, Pretus C, Quidé Y, Radua J, Ramos-Quiroga JA, Rasser PE, Reif A, Retico A, Roberts G, Rossell S, Rovaris DL, Rubia K, Sacchet M, Salavert J, Salvador R, Sarró S, Sawa A, Schall U, Scott R, Selvaggi P, Silk T, Sim K, Skoch A, Spalletta G, Spaniel F, Stein DJ, Steinsträter O, Stolicyn A, Takayanagi Y, Tamm L, Tavares M, Teumer A, Thiel K, Thomopoulos SI, Tomecek D, Tomyshev AS, Tordesillas-Gutiérrez D, Tosetti M, Uhlmann A, Van Rheenen T, Vazquez-Bourgón J, Vernooij MW, Vieta E, Vilarroya O, Weickert C, Weickert T, Westlye LT, Whalley H, Willinger D, Winter A, Wittfeld K, Yang TT, Yoncheva Y, Zijlmans JL, Hoogman M, Franke B, van Rooij D, Buitelaar J, Ching CRK, Andreassen OA, Pozzi E, Veltman D, Schmaal L, van Erp TGM, Turner J, Castellanos FX, Pausova Z, Thompson P, Paus T. Virtual Ontogeny of Cortical Growth Preceding Mental Illness. Biol Psychiatry 2022; 92:299-313. [PMID: 35489875 PMCID: PMC11080987 DOI: 10.1016/j.biopsych.2022.02.959] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 02/02/2022] [Accepted: 02/23/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.
Collapse
Affiliation(s)
- Yash Patel
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Jean Shin
- The Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Christoph Abé
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ingrid Agartz
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Dag Alnæs
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Linda A Antonucci
- Departments of Education Science, Psychology, Communication Science, University of Bari Aldo Moro, Bari, Italy
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Volker Arolt
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Guillaume Auzias
- National Centre for Scientific Research, Aix-Marseille University, Marseille, France
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Marques de Valdecilla University Hospital, Instituto de Investigación Valdecilla, CIBERSAM, School of Medicine, University of Cantabria, Santander, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Cibele Bandeira
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Zeynep Başgöze
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota
| | | | - Claiton H D Bau
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Jochen Bauer
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Alessandro Bertolino
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Caterina Del Mar Bonnin
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zürich, Zurich, Switzerland
| | | | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Juan R Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico
| | - Sara Calderoni
- Department of Developmental Neuroscience, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Rosa Calvo
- Institute of Neuroscience, Hospital Clinic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, Barcelona, Spain
| | | | - Dara M Cannon
- Clinical Neuroimaging Lab, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Susanna Carmona
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | | | - Stanley V Catts
- School of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Sneha Chenji
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Qian Hui Chew
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - David Coghill
- Department of Paediatrics, Department of Psychiatry, University of Melbourne, Parkville, Australia; Department of Psychiatry, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Colm G Connolly
- Department of Biomedical Sciences, Florida State University, Tallahassee, Florida
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, Virgen del Rocio University Hospital, Universidad de Sevilla, Instituto de Biomedicina de Sevilla, CIBERSAM, Sevilla, Spain
| | - Kathryn Cullen
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Christopher G Davey
- Department of Psychiatry, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Christine Deruelle
- National Centre for Scientific Research, Aix-Marseille University, Marseille, France
| | | | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Jeffery Epstein
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Tracy Erwin-Grabner
- Laboratory of Systems Neuroscience and Imaging in Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Jennifer Fedor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jacqueline Fitzgerald
- Trinity Institute of Neuroscience, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Judith M Ford
- San Francisco Veterans Affairs Medical Center, San Francisco, California
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | | | | | - Lisa Furlong
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Louise Gallagher
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Bingchen Gao
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jose M Goikolea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Ian Gotlib
- Department of Psychology, Stanford University, Stanford, California
| | - Roberto Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | | | - Eugenio H Grevet
- Department of Psychiatry, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nynke A Groenewold
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ben J Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
| | - Walter Heindel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Frans Henskens
- School of Medicine & Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Dirk J Heslenfeld
- Experimental and Clinical Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva Hilland
- Norwegian Centre for Mental Disorders Research NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pieter J Hoekstra
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Jonathan C Ipser
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Neda Jahanshad
- USC Mark and Mary Stevens Neuroimaging and Informatics Institute, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Babette Jakobi
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Andreas Jansen
- Core Facility Brain imaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Rune Jonassen
- Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway
| | - Anna Kaiser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - James Karantonis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Tilo Kircher
- Department of Psychiatry, Marburg University, Marburg, Germany
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Sheri-Michelle Koopowitz
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Mikael Landén
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | | | - Stephen Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Frank P MacMaster
- Departments of Psychiatry and Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Luigi A Maglanoc
- Department for Data Capture and Collections Management, University Center for Information Technology, University of Oslo, Oslo, Norway
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California
| | - Colm McDonald
- Galway Neuroscience Centre, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Andrew McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Patricia T Michie
- School of Psychology, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, New South Wales, Australia
| | | | - Ana Moreno-Alcázar
- FIDMAG Germanes Hospitalàries Research Foundation, Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Filippo Muratori
- Department of Developmental Neuroscience, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Leila Nabulsi
- Clinical Neuroimaging Lab, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | | | - Jaap Oosterlaan
- Clinical Neuropsychology Section, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, Victoria, Australia
| | - Mara Parellada
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Jose C Pariente
- Magnetic Resonance Imaging core facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Paul Pauli
- Department of Psychology (Biological Psychology, Clinical Psychology, and Psychotherapy), University of Würzburg, Würzburg, Germany
| | - Giulio Pergola
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Francesco Maria Piarulli
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Felipe Picon
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | | | - Clara Pretus
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - J Antoni Ramos-Quiroga
- Department of Psychiatry, Hospital Universitari Vall d'Hebrón, CIBERSAM, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Paul E Rasser
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt-Goethe University, Frankfurt am Main, Germany
| | | | | | - Susan Rossell
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Victoria, Australia
| | - Diego Luiz Rovaris
- Department of Physiology and Biophysics, Instituto de Ciencias Biomédicas Universidade de São Paulo, São Paulo, Brazil
| | - Katya Rubia
- Child & Adolescent Psychiatry, King's College London, London, United Kingdom
| | - Matthew Sacchet
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Josep Salavert
- FIDMAG Germanes Hospitalàries Research Foundation, Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
| | | | | | - Akira Sawa
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ulrich Schall
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Rodney Scott
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Pierluigi Selvaggi
- Azienda Ospedaliero-Universitaria Consorziale Policlinico di Bari, Bari, Italy
| | - Tim Silk
- School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Dan J Stein
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Olaf Steinsträter
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Leanne Tamm
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Maria Tavares
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
| | | | - Diana Tordesillas-Gutiérrez
- Department of Radiology, University Hospital Marqués de Valdecilla, Instituto de Investigación Valdecilla, Santander, Spain
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Anne Uhlmann
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany
| | - Tamsyn Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Javier Vazquez-Bourgón
- Department of Psychiatry, Marques de Valdecilla University Hospital, Instituto de Investigación Valdecilla, CIBERSAM, School of Medicine, University of Cantabria, Santander, Spain
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Eduard Vieta
- Institute of Neuroscience, Hospital Clinic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, Barcelona, Spain
| | - Oscar Vilarroya
- Department of Psychiatry, Autonomous University of Barcelona, Cerdanyola del Valles, Spain
| | - Cynthia Weickert
- Department of Neuroscience and Physiology, University of New South Wales, Sydney, Australia
| | | | - Lars T Westlye
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Heather Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - David Willinger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital, University of Zürich, Zurich, Switzerland
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases, Site Rostock/Greifswald, Greifswald, Germany
| | - Tony T Yang
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, University of California San Francisco, San Francisco, California
| | | | - Jendé L Zijlmans
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Daan van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Elena Pozzi
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Dick Veltman
- Department of Psychiatry, Amsterdam UMC, VUMC, Amsterdam, The Netherlands
| | - Lianne Schmaal
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | | | | | - Zdenka Pausova
- The Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Paul Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Tomas Paus
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada; Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montréal, Montreal, Quebec, Canada.
| |
Collapse
|
8
|
Ojha V, Nicosia G. Backpropagation Neural Tree. Neural Netw 2022; 149:66-83. [DOI: 10.1016/j.neunet.2022.02.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 08/22/2021] [Accepted: 02/03/2022] [Indexed: 11/17/2022]
|
9
|
Abstract
During evolution, the cerebral cortex advances by increasing in surface and the introduction of new cytoarchitectonic areas among which the prefrontal cortex (PFC) is considered to be the substrate of highest cognitive functions. Although neurons of the PFC are generated before birth, the differentiation of its neurons and development of synaptic connections in humans extend to the 3rd decade of life. During this period, synapses as well as neurotransmitter systems including their receptors and transporters, are initially overproduced followed by selective elimination. Advanced methods applied to human and animal models, enable investigation of the cellular mechanisms and role of specific genes, non-coding regulatory elements and signaling molecules in control of prefrontal neuronal production and phenotypic fate, as well as neuronal migration to establish layering of the PFC. Likewise, various genetic approaches in combination with functional assays and immunohistochemical and imaging methods reveal roles of neurotransmitter systems during maturation of the PFC. Disruption, or even a slight slowing of the rate of neuronal production, migration and synaptogenesis by genetic or environmental factors, can induce gross as well as subtle changes that eventually can lead to cognitive impairment. An understanding of the development and evolution of the PFC provide insight into the pathogenesis and treatment of congenital neuropsychiatric diseases as well as idiopathic developmental disorders that cause intellectual disabilities.
Collapse
Affiliation(s)
- Sharon M Kolk
- Department of Molecular Neurobiology, Donders Institute for Brain, Cognition and Behaviour and Faculty of Science, Radboud University, Nijmegen, The Netherlands.
| | - Pasko Rakic
- Department of Neuroscience and Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut, USA.
| |
Collapse
|
10
|
Zoh Y, Chang SWC, Crockett MJ. The prefrontal cortex and (uniquely) human cooperation: a comparative perspective. Neuropsychopharmacology 2022; 47:119-133. [PMID: 34413478 PMCID: PMC8617274 DOI: 10.1038/s41386-021-01092-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/03/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023]
Abstract
Humans have an exceptional ability to cooperate relative to many other species. We review the neural mechanisms supporting human cooperation, focusing on the prefrontal cortex. One key feature of human social life is the prevalence of cooperative norms that guide social behavior and prescribe punishment for noncompliance. Taking a comparative approach, we consider shared and unique aspects of cooperative behaviors in humans relative to nonhuman primates, as well as divergences in brain structure that might support uniquely human aspects of cooperation. We highlight a medial prefrontal network common to nonhuman primates and humans supporting a foundational process in cooperative decision-making: valuing outcomes for oneself and others. This medial prefrontal network interacts with lateral prefrontal areas that are thought to represent cooperative norms and modulate value representations to guide behavior appropriate to the local social context. Finally, we propose that more recently evolved anterior regions of prefrontal cortex play a role in arbitrating between cooperative norms across social contexts, and suggest how future research might fruitfully examine the neural basis of norm arbitration.
Collapse
Affiliation(s)
- Yoonseo Zoh
- grid.47100.320000000419368710Department of Psychology, Yale University, New Haven, USA
| | - Steve W. C. Chang
- grid.47100.320000000419368710Department of Psychology, Yale University, New Haven, USA
| | - Molly J. Crockett
- grid.47100.320000000419368710Department of Psychology, Yale University, New Haven, USA
| |
Collapse
|
11
|
Connecting the Neurobiology of Developmental Brain Injury: Neuronal Arborisation as a Regulator of Dysfunction and Potential Therapeutic Target. Int J Mol Sci 2021; 22:ijms22158220. [PMID: 34360985 PMCID: PMC8348801 DOI: 10.3390/ijms22158220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 07/23/2021] [Accepted: 07/28/2021] [Indexed: 11/17/2022] Open
Abstract
Neurodevelopmental disorders can derive from a complex combination of genetic variation and environmental pressures on key developmental processes. Despite this complex aetiology, and the equally complex array of syndromes and conditions diagnosed under the heading of neurodevelopmental disorder, there are parallels in the neuropathology of these conditions that suggest overlapping mechanisms of cellular injury and dysfunction. Neuronal arborisation is a process of dendrite and axon extension that is essential for the connectivity between neurons that underlies normal brain function. Disrupted arborisation and synapse formation are commonly reported in neurodevelopmental disorders. Here, we summarise the evidence for disrupted neuronal arborisation in these conditions, focusing primarily on the cortex and hippocampus. In addition, we explore the developmentally specific mechanisms by which neuronal arborisation is regulated. Finally, we discuss key regulators of neuronal arborisation that could link to neurodevelopmental disease and the potential for pharmacological modification of arborisation and the formation of synaptic connections that may provide therapeutic benefit in the future.
Collapse
|
12
|
Dimitrova R, Arulkumaran S, Carney O, Chew A, Falconer S, Ciarrusta J, Wolfers T, Batalle D, Cordero-Grande L, Price AN, Teixeira RPAG, Hughes E, Egloff A, Hutter J, Makropoulos A, Robinson EC, Schuh A, Vecchiato K, Steinweg JK, Macleod R, Marquand AF, McAlonan G, Rutherford MA, Counsell SJ, Smith SM, Rueckert D, Hajnal JV, O’Muircheartaigh J, Edwards AD. Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts. Cereb Cortex 2021; 31:3665-3677. [PMID: 33822913 PMCID: PMC8258435 DOI: 10.1093/cercor/bhab039] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/15/2021] [Accepted: 02/05/2021] [Indexed: 12/20/2022] Open
Abstract
The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.
Collapse
Affiliation(s)
- Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Sophie Arulkumaran
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Judit Ciarrusta
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Thomas Wolfers
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen 6525EN, the Netherlands
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicacion, Universidad Politecnica de Madrid and CIBER-BBN, Madrid 28040, Spain
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Rui P A G Teixeira
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Antonios Makropoulos
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Johannes K Steinweg
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Russell Macleod
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen 6525EN, the Netherlands
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
- South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Stephen M Smith
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| |
Collapse
|
13
|
Ball G, Seidlitz J, O’Muircheartaigh J, Dimitrova R, Fenchel D, Makropoulos A, Christiaens D, Schuh A, Passerat-Palmbach J, Hutter J, Cordero-Grande L, Hughes E, Price A, Hajnal JV, Rueckert D, Robinson EC, Edwards AD. Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain. PLoS Biol 2020; 18:e3000976. [PMID: 33226978 PMCID: PMC7721147 DOI: 10.1371/journal.pbio.3000976] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 12/07/2020] [Accepted: 11/02/2020] [Indexed: 02/07/2023] Open
Abstract
Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder. Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. A large neuroimaging study of newborn infants reveals how their cortical structure at birth is associated with patterns of gene expression in the fetal cortex and how this relationship is affected by preterm birth.
Collapse
Affiliation(s)
- Gareth Ball
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, Australia
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
- * E-mail:
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, United States of America
- Department of Psychiatry, University of Cambridge, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Daphna Fenchel
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Antonios Makropoulos
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Daan Christiaens
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Belgium
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, United Kingdom
| | | | - Jana Hutter
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Anthony Price
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Jo V. Hajnal
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, United Kingdom
| | - Emma C. Robinson
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, King’s College London, United Kingdom
| |
Collapse
|
14
|
Holyoak KJ, Monti MM. Relational Integration in the Human Brain: A Review and Synthesis. J Cogn Neurosci 2020; 33:341-356. [PMID: 32762521 DOI: 10.1162/jocn_a_01619] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Relational integration is required when multiple explicit representations of relations between entities must be jointly considered to make inferences. We provide an overview of the neural substrate of relational integration in humans and the processes that support it, focusing on work on analogical and deductive reasoning. In addition to neural evidence, we consider behavioral and computational work that has informed neural investigations of the representations of individual relations and of relational integration. In very general terms, evidence from neuroimaging, neuropsychological, and neuromodulatory studies points to a small set of regions (generally left lateralized) that appear to constitute key substrates for component processes of relational integration. These include posterior parietal cortex, implicated in the representation of first-order relations (e.g., A:B); rostrolateral pFC, apparently central in integrating first-order relations so as to generate and/or evaluate higher-order relations (e.g., A:B::C:D); dorsolateral pFC, involved in maintaining relations in working memory; and ventrolateral pFC, implicated in interference control (e.g., inhibiting salient information that competes with relevant relations). Recent work has begun to link computational models of relational representation and reasoning with patterns of neural activity within these brain areas.
Collapse
|
15
|
Ferradal SL, Gagoski B, Jaimes C, Yi F, Carruthers C, Vu C, Litt JS, Larsen R, Sutton B, Grant PE, Zöllei L. System-Specific Patterns of Thalamocortical Connectivity in Early Brain Development as Revealed by Structural and Functional MRI. Cereb Cortex 2020; 29:1218-1229. [PMID: 29425270 DOI: 10.1093/cercor/bhy028] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Indexed: 01/31/2023] Open
Abstract
The normal development of thalamocortical connections plays a critical role in shaping brain connectivity in the prenatal and postnatal periods. Recent studies using advanced magnetic resonance imaging (MRI) techniques in neonates and infants have shown that abnormal thalamocortical connectivity is associated with adverse neurodevelopmental outcomes. However, all these studies have focused on a single neuroimaging modality, overlooking the dynamic relationship between structure and function at this early stage. Here, we study the relationship between structural and functional thalamocortical connectivity patterns derived from healthy full-term infants scanned with diffusion-weighted MRI and resting-state functional MRI within the first weeks of life (mean gestational age = 39.3 ± 1.2 weeks; age at scan = 24.2 ± 7.9 days). Our results show that while there is, in general, good spatial agreement between both MRI modalities, there are regional variations that are system-specific: regions involving primary-sensory cortices exhibit greater structural/functional overlap, whereas higher-order association areas such as temporal and posterior parietal cortices show divergence in spatial patterns of each modality. This variability illustrates the complementarity of both modalities and highlights the importance of multimodal approaches.
Collapse
Affiliation(s)
| | - Borjan Gagoski
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Camilo Jaimes
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Francesca Yi
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Catherine Vu
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Ryan Larsen
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Brad Sutton
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - P Ellen Grant
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lilla Zöllei
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
16
|
Bauernfeind AL, Babbitt CC. Metabolic changes in human brain evolution. Evol Anthropol 2020; 29:201-211. [PMID: 32329960 DOI: 10.1002/evan.21831] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 08/30/2019] [Accepted: 03/13/2020] [Indexed: 12/23/2022]
Abstract
Because the human brain is considerably larger than those of other primates, it is not surprising that its energy requirements would far exceed that of any of the species within the order. Recently, the development of stem cell technologies and single-cell transcriptomics provides novel ways to address the question of what specific genomic changes underlie the human brain's unique phenotype. In this review, we consider what is currently known about human brain metabolism using a variety of methods from brain imaging and stereology to transcriptomics. Next, we examine novel opportunities that stem cell technologies and single-cell transcriptomics provide to further our knowledge of human brain energetics. These new experimental approaches provide the ability to elucidate the functional effects of changes in genetic sequence and expression levels that potentially had a profound impact on the evolution of the human brain.
Collapse
Affiliation(s)
- Amy L Bauernfeind
- Department of Neuroscience, Washington University Medical School, St. Louis, Missouri, USA.,Department of Anthropology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Courtney C Babbitt
- Department of Biology, University of Massachusetts Amherst, Amherst, Massachusetts, USA
| |
Collapse
|
17
|
Bates AS, Manton JD, Jagannathan SR, Costa M, Schlegel P, Rohlfing T, Jefferis GSXE. The natverse, a versatile toolbox for combining and analysing neuroanatomical data. eLife 2020; 9:e53350. [PMID: 32286229 PMCID: PMC7242028 DOI: 10.7554/elife.53350] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 04/11/2020] [Indexed: 11/18/2022] Open
Abstract
To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.
Collapse
Affiliation(s)
| | - James D Manton
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | - Sridhar R Jagannathan
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Marta Costa
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Torsten Rohlfing
- SRI International, Neuroscience Program, Center for Health SciencesMenlo ParkUnited States
| | - Gregory SXE Jefferis
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| |
Collapse
|
18
|
Farhoodi R, Lansdell BJ, Kording KP. Quantifying How Staining Methods Bias Measurements of Neuron Morphologies. Front Neuroinform 2019; 13:36. [PMID: 31191283 PMCID: PMC6541099 DOI: 10.3389/fninf.2019.00036] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Accepted: 04/25/2019] [Indexed: 12/20/2022] Open
Abstract
The process through which neurons are labeled is a key methodological choice in measuring neuron morphology. However, little is known about how this choice may bias measurements. To quantify this bias we compare the extracted morphology of neurons collected from the same rodent species, experimental condition, gender distribution, age distribution, brain region and putative cell type, but obtained with 19 distinct staining methods. We found strong biases on measured features of morphology. These were largest in features related to the coverage of the dendritic tree (e.g., the total dendritic tree length). Understanding measurement biases is crucial for interpreting morphological data.
Collapse
Affiliation(s)
- Roozbeh Farhoodi
- Department of Mathematics, Sharif University of Technology, Tehran, Iran
| | | | - Konrad Paul Kording
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States.,Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, United States
| |
Collapse
|
19
|
Lebenberg J, Mangin JF, Thirion B, Poupon C, Hertz-Pannier L, Leroy F, Adibpour P, Dehaene-Lambertz G, Dubois J. Mapping the asynchrony of cortical maturation in the infant brain: A MRI multi-parametric clustering approach. Neuroimage 2019; 185:641-653. [DOI: 10.1016/j.neuroimage.2018.07.022] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 07/02/2018] [Accepted: 07/10/2018] [Indexed: 12/28/2022] Open
|
20
|
Kostović I, Sedmak G, Judaš M. Neural histology and neurogenesis of the human fetal and infant brain. Neuroimage 2018; 188:743-773. [PMID: 30594683 DOI: 10.1016/j.neuroimage.2018.12.043] [Citation(s) in RCA: 102] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 12/18/2018] [Accepted: 12/20/2018] [Indexed: 01/11/2023] Open
Abstract
The human brain develops slowly and over a long period of time which lasts for almost three decades. This enables good spatio-temporal resolution of histogenetic and neurogenetic events as well as an appropriate and clinically relevant timing of these events. In order to successfully apply in vivo neuroimaging data, in analyzing both the normal brain development and the neurodevelopmental origin of major neurological and mental disorders, it is important to correlate these neuroimaging data with the existing data on morphogenetic, histogenetic and neurogenetic events. Furthermore, when performing such correlation, the genetic, genomic, and molecular biology data on phenotypic specification of developing brain regions, areas and neurons should also be included. In this review, we focus on early developmental periods (form 8 postconceptional weeks to the second postnatal year) and describe the microstructural organization and neural circuitry elements of the fetal and early postnatal human cerebrum.
Collapse
Affiliation(s)
- I Kostović
- University of Zagreb School of Medicine, Croatian Institute for Brain Research, Centre of Excellence for Basic, Clinical and Translational Neuroscience, Šalata 12, 10000, Zagreb, Croatia.
| | - G Sedmak
- University of Zagreb School of Medicine, Croatian Institute for Brain Research, Centre of Excellence for Basic, Clinical and Translational Neuroscience, Šalata 12, 10000, Zagreb, Croatia.
| | - M Judaš
- University of Zagreb School of Medicine, Croatian Institute for Brain Research, Centre of Excellence for Basic, Clinical and Translational Neuroscience, Šalata 12, 10000, Zagreb, Croatia.
| |
Collapse
|
21
|
Koch SB, Mars RB, Toni I, Roelofs K. Emotional control, reappraised. Neurosci Biobehav Rev 2018; 95:528-534. [DOI: 10.1016/j.neubiorev.2018.11.003] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 09/17/2018] [Accepted: 11/05/2018] [Indexed: 12/11/2022]
|
22
|
Thiebaut de Schotten M, Urbanski M, Batrancourt B, Levy R, Dubois B, Cerliani L, Volle E. Rostro-caudal Architecture of the Frontal Lobes in Humans. Cereb Cortex 2018; 27:4033-4047. [PMID: 27461122 DOI: 10.1093/cercor/bhw215] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Accepted: 06/20/2016] [Indexed: 11/12/2022] Open
Abstract
The nature of the inputs and outputs of a brain region defines its functional specialization. The frontal portion of the brain is essential for goal-directed behaviors, however, the biological basis for its functional organization is unknown. Here, exploring structural connectomic properties, we delineated 12 frontal areas, defined by the pattern of their white matter connections. This result was highly reproducible across neuroimaging centers, acquisition parameters, and participants. These areas corresponded to regions functionally engaged in specific tasks, organized along a rostro-caudal axis from the most complex high-order association areas to the simplest idiotopic areas. The rostro-caudal axis along which the 12 regions were organized also reflected a gradient of cortical thickness, myelination, and cell body density. Importantly, across the identified regions, this gradient of microstructural features was strongly associated with the varying degree of information processing complexity. These new anatomical signatures shed light onto the structural organization of the frontal lobes and could help strengthen the prediction or diagnosis of neurodevelopmental and neurodegenerative disorders.
Collapse
Affiliation(s)
- Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Group, Brain and Spine Institute, Paris, France.,Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France.,Centre de Neuroimagerie de Recherche CENIR, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Marika Urbanski
- Brain Connectivity and Behaviour Group, Brain and Spine Institute, Paris, France.,Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France.,Service de Médecine et de Réadaptation, Hôpitaux de Saint-Maurice, Saint-Maurice, France
| | - Benedicte Batrancourt
- Brain Connectivity and Behaviour Group, Brain and Spine Institute, Paris, France.,Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Richard Levy
- Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Bruno Dubois
- Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Leonardo Cerliani
- Brain Connectivity and Behaviour Group, Brain and Spine Institute, Paris, France.,Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Emmanuelle Volle
- Brain Connectivity and Behaviour Group, Brain and Spine Institute, Paris, France.,Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France.,Centre de Neuroimagerie de Recherche CENIR, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| |
Collapse
|
23
|
Bouyssi-Kobar M, Brossard-Racine M, Jacobs M, Murnick J, Chang T, Limperopoulos C. Regional microstructural organization of the cerebral cortex is affected by preterm birth. Neuroimage Clin 2018; 18:871-880. [PMID: 29876271 PMCID: PMC5988027 DOI: 10.1016/j.nicl.2018.03.020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Revised: 03/09/2018] [Accepted: 03/15/2018] [Indexed: 10/31/2022]
Abstract
Objectives To compare regional cerebral cortical microstructural organization between preterm infants at term-equivalent age (TEA) and healthy full-term newborns, and to examine the impact of clinical risk factors on cerebral cortical micro-organization in the preterm cohort. Study design We prospectively enrolled very preterm infants (gestational age (GA) at birth<32 weeks; birthweight<1500 g) and healthy full-term controls. Using non-invasive 3T diffusion tensor imaging (DTI) metrics, we quantified regional micro-organization in ten cerebral cortical areas: medial/dorsolateral prefrontal cortex, anterior/posterior cingulate cortex, insula, posterior parietal cortex, motor/somatosensory/auditory/visual cortex. ANCOVA analyses were performed controlling for sex and postmenstrual age at MRI. Results We studied 91 preterm infants at TEA and 69 full-term controls. Preterm infants demonstrated significantly higher diffusivity in the prefrontal, parietal, motor, somatosensory, and visual cortices suggesting delayed maturation of these cortical areas. Additionally, postnatal hydrocortisone treatment was related to accelerated microstructural organization in the prefrontal and somatosensory cortices. Conclusions Preterm birth alters regional microstructural organization of the cerebral cortex in both neurocognitive brain regions and areas with primary sensory/motor functions. We also report for the first time a potential protective effect of postnatal hydrocortisone administration on cerebral cortical development in preterm infants.
Collapse
Affiliation(s)
- Marine Bouyssi-Kobar
- The Developing Brain Research Laboratory, Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC 20010, USA; Institute for Biomedical Sciences, George Washington University, Washington, DC 20037, USA.
| | - Marie Brossard-Racine
- Department of Pediatrics Neurology, McGill University Health Center, Montreal, QC H4A3J1, Canada.
| | - Marni Jacobs
- Division of Biostatistics and Study Methodology, Children's Research Institute, Children's National Health System, Washington, DC 20010, USA.
| | - Jonathan Murnick
- The Developing Brain Research Laboratory, Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC 20010, USA.
| | - Taeun Chang
- Department of Neurology, Children's National Health System, Washington, DC 20010, USA.
| | - Catherine Limperopoulos
- The Developing Brain Research Laboratory, Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC 20010, USA.
| |
Collapse
|
24
|
Weir RK, Bauman MD, Jacobs B, Schumann CM. Protracted dendritic growth in the typically developing human amygdala and increased spine density in young ASD brains. J Comp Neurol 2017; 526:262-274. [PMID: 28929566 DOI: 10.1002/cne.24332] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 09/01/2017] [Accepted: 09/04/2017] [Indexed: 12/14/2022]
Abstract
The amygdala is a medial temporal lobe structure implicated in social and emotional regulation. In typical development (TD), the amygdala continues to increase volumetrically throughout childhood and into adulthood, while other brain structures are stable or decreasing in volume. In autism spectrum disorder (ASD), the amygdala undergoes rapid early growth, making it volumetrically larger in children with ASD compared to TD children. Here we explore: (a) if dendritic arborization in the amygdala follows the pattern of protracted growth in TD and early overgrowth in ASD and (b), if spine density in the amygdala in ASD cases differs from TD from youth to adulthood. The amygdala from 32 postmortem human brains (7-46 years of age) were stained using a Golgi-Kopsch impregnation. Ten principal neurons per case were selected in the lateral nucleus and traced using Neurolucida software in their entirety. We found that both ASD and TD individuals show a similar pattern of increasing dendritic length with age well into adulthood. However, spine density is (a) greater in young ASD cases compared to age-matched TD controls (<18 years old) and (b) decreases in the amygdala as people with ASD age into adulthood, a phenomenon not found in TD. Therefore, by adulthood, there is no observable difference in spine density in the amygdala between ASD and TD age-matched adults (≥18 years old). Our findings highlight the unique growth trajectory of the amygdala and suggest that spine density may contribute to aberrant development and function of the amygdala in children with ASD.
Collapse
Affiliation(s)
- R K Weir
- Department of Psychiatry and Behavioral Sciences, University of California at Davis MIND Institute, Sacramento, California
| | - M D Bauman
- Department of Psychiatry and Behavioral Sciences, University of California at Davis MIND Institute, Sacramento, California
| | - B Jacobs
- Laboratory of Quantitative Neuromorphology, Department of Psychology, Colorado College, Colorado Springs, Colorado
| | - C M Schumann
- Department of Psychiatry and Behavioral Sciences, University of California at Davis MIND Institute, Sacramento, California
| |
Collapse
|
25
|
Affiliation(s)
- Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052
| | - Aida Gómez-Robles
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052
- Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, United Kingdom
| |
Collapse
|
26
|
Hrvoj-Mihic B, Hanson KL, Lew CH, Stefanacci L, Jacobs B, Bellugi U, Semendeferi K. Basal Dendritic Morphology of Cortical Pyramidal Neurons in Williams Syndrome: Prefrontal Cortex and Beyond. Front Neurosci 2017; 11:419. [PMID: 28848376 PMCID: PMC5554499 DOI: 10.3389/fnins.2017.00419] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 07/05/2017] [Indexed: 12/26/2022] Open
Abstract
Williams syndrome (WS) is a unique neurodevelopmental disorder with a specific behavioral and cognitive profile, which includes hyperaffiliative behavior, poor social judgment, and lack of social inhibition. Here we examined the morphology of basal dendrites on pyramidal neurons in the cortex of two rare adult subjects with WS. Specifically, we examined two areas in the prefrontal cortex (PFC)-the frontal pole (Brodmann area 10) and the orbitofrontal cortex (Brodmann area 11)-and three areas in the motor, sensory, and visual cortex (BA 4, BA 3-1-2, BA 18). The findings suggest that the morphology of basal dendrites on the pyramidal neurons is altered in the cortex of WS, with differences that were layer-specific, more prominent in PFC areas, and displayed an overall pattern of dendritic organization that differentiates WS from other disorders. In particular, and unlike what was expected based on typically developing brains, basal dendrites in the two PFC areas did not display longer and more branched dendrites compared to motor, sensory and visual areas. Moreover, dendritic branching, dendritic length, and the number of dendritic spines differed little within PFC and between the central executive region (BA 10) and BA 11 that is part of the orbitofrontal region involved into emotional processing. In contrast, the relationship between the degree of neuronal branching in supra- versus infra-granular layers was spared in WS. Although this study utilized tissue held in formalin for a prolonged period of time and the number of neurons available for analysis was limited, our findings indicate that WS cortex, similar to that in other neurodevelopmental disorders such as Down syndrome, Rett syndrome, Fragile X, and idiopathic autism, has altered morphology of basal dendrites on pyramidal neurons, which appears more prominent in selected areas of the PFC. Results were examined from developmental perspectives and discussed in the context of other neurodevelopmental disorders. We have proposed hypotheses for further investigations of morphological changes on basal dendrites in WS, a syndrome of particular interest given its unique social and cognitive phenotype.
Collapse
Affiliation(s)
- Branka Hrvoj-Mihic
- Department of Anthropology, University of California, San DiegoSan Diego, La Jolla, CA, United States
| | - Kari L Hanson
- Department of Anthropology, University of California, San DiegoSan Diego, La Jolla, CA, United States
| | - Caroline H Lew
- Department of Anthropology, University of California, San DiegoSan Diego, La Jolla, CA, United States
| | - Lisa Stefanacci
- Department of Anthropology, University of California, San DiegoSan Diego, La Jolla, CA, United States
| | - Bob Jacobs
- Neuroscience Program, Colorado CollegeColorado Springs, CO, United States
| | - Ursula Bellugi
- Laboratory for Cognitive Neuroscience, The Salk Institute for Biological StudiesLa Jolla, CA, United States
| | - Katerina Semendeferi
- Department of Anthropology, University of California, San DiegoSan Diego, La Jolla, CA, United States.,Kavli Institute for Brain and Mind, University of California, San DiegoSan Diego, La Jolla, CA, United States
| |
Collapse
|
27
|
Friedrichs-Maeder CL, Griffa A, Schneider J, Hüppi PS, Truttmann A, Hagmann P. Exploring the role of white matter connectivity in cortex maturation. PLoS One 2017; 12:e0177466. [PMID: 28545040 PMCID: PMC5435226 DOI: 10.1371/journal.pone.0177466] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 04/27/2017] [Indexed: 12/18/2022] Open
Abstract
The maturation of the cortical gray matter (GM) and white matter (WM) are described as sequential processes following multiple, but distinct rules. However, neither the mechanisms driving brain maturation processes, nor the relationship between GM and WM maturation are well understood. Here we use connectomics and two MRI measures reflecting maturation related changes in cerebral microstructure, namely the Apparent Diffusion Coefficient (ADC) and the T1 relaxation time (T1), to study brain development. We report that the advancement of GM and WM maturation are inter-related and depend on the underlying brain connectivity architecture. Particularly, GM regions and their incident WM connections show corresponding maturation levels, which is also observed for GM regions connected through a WM tract. Based on these observations, we propose a simple computational model supporting a key role for the connectome in propagating maturation signals sequentially from external stimuli, through primary sensory structures to higher order functional cortices.
Collapse
Affiliation(s)
| | - Alessandra Griffa
- Department of Radiology, Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne, Switzerland
- Signal Processing Laboratory (LTSS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Juliane Schneider
- Clinic of Neonatology and Follow-up, Department of Pediatrics, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Petra Susan Hüppi
- Division of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland
| | - Anita Truttmann
- Clinic of Neonatology and Follow-up, Department of Pediatrics, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne, Switzerland
- Signal Processing Laboratory (LTSS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| |
Collapse
|
28
|
Snow PJ. The Structural and Functional Organization of Cognition. Front Hum Neurosci 2016; 10:501. [PMID: 27799901 PMCID: PMC5065967 DOI: 10.3389/fnhum.2016.00501] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2016] [Accepted: 09/22/2016] [Indexed: 12/13/2022] Open
Abstract
This article proposes that what have been historically and contemporarily defined as different domains of human cognition are served by one of four functionally- and structurally-distinct areas of the prefrontal cortex (PFC). Their contributions to human intelligence are as follows: (a) BA9, enables our emotional intelligence, engaging the psychosocial domain; (b) BA47, enables our practical intelligence, engaging the material domain; (c) BA46 (or BA46-9/46), enables our abstract intelligence, engaging the hypothetical domain; and (d) BA10, enables our temporal intelligence, engaging in planning within any of the other three domains. Given their unique contribution to human cognition, it is proposed that these areas be called the, social (BA9), material (BA47), abstract (BA46-9/46) and temporal (BA10) mind. The evidence that BA47 participates strongly in verbal and gestural communication suggests that language evolved primarily as a consequence of the extreme selective pressure for practicality; an observation supported by the functional connectivity between BA47 and orbital areas that negatively reinforce lying. It is further proposed that the abstract mind (BA46-9/46) is the primary seat of metacognition charged with creating adaptive behavioral strategies by generating higher-order concepts (hypotheses) from lower-order concepts originating from the other three domains of cognition.
Collapse
Affiliation(s)
- Peter J Snow
- School of Medical Science, Griffith University Gold Coast, QLD, Australia
| |
Collapse
|
29
|
Jacobs B, Lee L, Schall M, Raghanti MA, Lewandowski AH, Kottwitz JJ, Roberts JF, Hof PR, Sherwood CC. Neocortical neuronal morphology in the newborn giraffe (Giraffa camelopardalis tippelskirchi) and African elephant (Loxodonta africana). J Comp Neurol 2015; 524:257-87. [DOI: 10.1002/cne.23841] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 06/19/2015] [Accepted: 06/22/2015] [Indexed: 12/20/2022]
Affiliation(s)
- Bob Jacobs
- Laboratory of Quantitative Neuromorphology Department of Psychology, Colorado College; Colorado Springs Colorado 80903
| | - Laura Lee
- Laboratory of Quantitative Neuromorphology Department of Psychology, Colorado College; Colorado Springs Colorado 80903
| | - Matthew Schall
- Laboratory of Quantitative Neuromorphology Department of Psychology, Colorado College; Colorado Springs Colorado 80903
| | | | | | - Jack J. Kottwitz
- Department of Anatomy, Physiology, and Pharmacology, College of Veterinary Medicine; Auburn University; Auburn Alabama 36849
| | - John F. Roberts
- Thompson Bishop Sparks State Diagnostic Laboratory Alabama Department of Agriculture and Industries; Auburn Alabama 36849
| | - Patrick R. Hof
- Fishberg Department of Neuroscience and Friedman Brain Institute; Icahn School of Medicine at Mount Sinai; New York New York 10029
| | - Chet C. Sherwood
- Department of Anthropology; The George Washington University; Washington DC 20052
| |
Collapse
|
30
|
Smyser TA, Smyser CD, Rogers CE, Gillespie SK, Inder TE, Neil JJ. Cortical Gray and Adjacent White Matter Demonstrate Synchronous Maturation in Very Preterm Infants. Cereb Cortex 2015. [PMID: 26209848 DOI: 10.1093/cercor/bhv164] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Spatial and functional gradients of development have been described for the maturation of cerebral gray and white matter using histological and radiological approaches. We evaluated these patterns in very preterm (VPT) infants using diffusion tensor imaging. Data were obtained from 3 groups: 1) 22 VPT infants without white matter injury (WMI), of whom all had serial MRI studies during the neonatal period, 2) 19 VPT infants with WMI, of whom 3 had serial MRI studies and 3) 12 healthy, term-born infants. Regions of interest were placed in the cortical gray and adjacent white matter in primary motor, primary visual, visual association, and prefrontal regions. From the MRI data at term-equivalent postmenstrual age, differences in mean diffusivity were found in all areas between VPT infants with WMI and the other 2 groups. In contrast, minimal differences in fractional anisotropy were found between the 3 groups. These findings suggest that cortical maturation is delayed in VPT infants with WMI when compared with term control infants and VPT infants without WMI. From the serial MRI data from VPT infants, synchronous development between gray and white matter was evident in all areas and all groups, with maturation in primary motor and sensory regions preceding that of association areas. This finding highlights the regionally varying but locally synchronous nature of the development of cortical gray matter and its adjacent white matter.
Collapse
Affiliation(s)
| | - Christopher D Smyser
- Department of Neurology
- Department of Pediatrics
- Department of Radiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | | | - Sarah K Gillespie
- Department of Radiology, Washington University School of Medicine, St Louis, MO 63110, USA
- University College, Washington University, St Louis, MO 63110, USA
| | - Terrie E Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Jeffrey J Neil
- Department of Neurology, Boston Children's Hospital, Boston, MA 02115, USA
| |
Collapse
|
31
|
Specialization and integration of functional thalamocortical connectivity in the human infant. Proc Natl Acad Sci U S A 2015; 112:6485-90. [PMID: 25941391 DOI: 10.1073/pnas.1422638112] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Connections between the thalamus and cortex develop rapidly before birth, and aberrant cerebral maturation during this period may underlie a number of neurodevelopmental disorders. To define functional thalamocortical connectivity at the normal time of birth, we used functional MRI (fMRI) to measure blood oxygen level-dependent (BOLD) signals in 66 infants, 47 of whom were at high risk of neurocognitive impairment because of birth before 33 wk of gestation and 19 of whom were term infants. We segmented the thalamus based on correlation with functionally defined cortical components using independent component analysis (ICA) and seed-based correlations. After parcellating the cortex using ICA and segmenting the thalamus based on dominant connections with cortical parcellations, we observed a near-facsimile of the adult functional parcellation. Additional analysis revealed that BOLD signal in heteromodal association cortex typically had more widespread and overlapping thalamic representations than primary sensory cortex. Notably, more extreme prematurity was associated with increased functional connectivity between thalamus and lateral primary sensory cortex but reduced connectivity between thalamus and cortex in the prefrontal, insular and anterior cingulate regions. This work suggests that, in early infancy, functional integration through thalamocortical connections depends on significant functional overlap in the topographic organization of the thalamus and that the experience of premature extrauterine life modulates network development, altering the maturation of networks thought to support salience, executive, integrative, and cognitive functions.
Collapse
|
32
|
Abstract
Advances in methodology have led to expanded application of resting-state functional MRI (rs-fMRI) to the study of term and prematurely born infants during the first years of life, providing fresh insight into the earliest forms of functional cerebral development. In this review, we detail our evolving understanding of the use of rs-fMRI for studying neonates. We initially focus on the biological processes of cortical development related to resting-state network development. We then review technical issues principally affecting neonatal investigations, including the effects of subject motion during acquisition and image distortions related to magnetic susceptibility effects. We next summarize the literature in which rs-fMRI is used to study normal brain development during the early postnatal period, the effects of prematurity, and the effects of cerebral injury. Finally, we review potential future directions for the field, such as the use of complementary imaging modalities and advanced analysis techniques.
Collapse
Affiliation(s)
- Christopher D. Smyser
- Division of Pediatric Neurology, Department of Neurology, Washington University School of Medicine, St. Louis, MO
| | - Jeffrey J. Neil
- Department of Neurology, Boston Children’s Hospital, Boston, MA,Corresponding author. Jeff Neil, MD, PhD, Neurology, Boston Children's Hospital, 333 Longwood Avenue, LO 450, Boston, MA 02115, phone (617) 355-6388, fax (617) 730-0284,
| |
Collapse
|
33
|
Khundrakpam BS, Tohka J, Evans AC. Prediction of brain maturity based on cortical thickness at different spatial resolutions. Neuroimage 2015; 111:350-9. [PMID: 25731999 DOI: 10.1016/j.neuroimage.2015.02.046] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Revised: 02/09/2015] [Accepted: 02/19/2015] [Indexed: 11/18/2022] Open
Abstract
Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity.
Collapse
Affiliation(s)
| | - Jussi Tohka
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Spain
| | - Alan C Evans
- Montreal Neurological Institute, McGill University, Montreal, Canada
| |
Collapse
|
34
|
Bauernfeind AL, Babbitt CC. The appropriation of glucose through primate neurodevelopment. J Hum Evol 2014; 77:132-40. [DOI: 10.1016/j.jhevol.2014.05.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2014] [Revised: 03/22/2014] [Accepted: 05/02/2014] [Indexed: 12/25/2022]
|
35
|
Charvet CJ, Finlay BL. Evo-devo and the primate isocortex: the central organizing role of intrinsic gradients of neurogenesis. BRAIN, BEHAVIOR AND EVOLUTION 2014; 84:81-92. [PMID: 25247448 DOI: 10.1159/000365181] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Spatial gradients in the initiation and termination of basic processes, such as cytogenesis, cell-type specification and dendritic maturation, are ubiquitous in developing nervous systems. Such gradients can produce a niche adaptation in a particular species. For example, the high density of photoreceptors and neurons in the 'area centralis' of some vertebrate retinas result from the early maturation of its center relative to its periphery. Across species, regularities in allometric scaling of brain regions can derive from conserved spatial gradients: longer neurogenesis in the alar versus the basal plate of the neural tube is associated with relatively greater expansion of alar plate derivatives in larger brains. We describe gradients of neurogenesis within the isocortex and their effects on adult cytoarchitecture within and across species. Longer duration of neurogenesis in the caudal isocortex is associated with increased neuron number and density per column relative to the rostral isocortex. Later-maturing features of single neurons, such as soma size and dendritic spine numbers reflect this gradient. Considering rodents and primates, the longer the duration of isocortical neurogenesis in each species, the greater the rostral-to-caudal difference in neuron number and density per column. Extended developmental duration produces substantial, predictable changes in the architecture of the isocortex in larger brains, and presumably a progressively changed functional organization, the properties of which we do not yet fully understand. Many features of isocortical architecture previously viewed as species- or niche-specific adaptations can now be integrated as the natural outcomes of spatiotemporal gradients that are deployed in larger brains.
Collapse
Affiliation(s)
- Christine J Charvet
- Behavioral and Evolutionary Neuroscience Group, Department of Psychology, Cornell University, Ithaca, N.Y., USA
| | | |
Collapse
|
36
|
Elston GN, Fujita I. Pyramidal cell development: postnatal spinogenesis, dendritic growth, axon growth, and electrophysiology. Front Neuroanat 2014; 8:78. [PMID: 25161611 PMCID: PMC4130200 DOI: 10.3389/fnana.2014.00078] [Citation(s) in RCA: 109] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2014] [Accepted: 07/22/2014] [Indexed: 01/12/2023] Open
Abstract
Here we review recent findings related to postnatal spinogenesis, dendritic and axon growth, pruning and electrophysiology of neocortical pyramidal cells in the developing primate brain. Pyramidal cells in sensory, association and executive cortex grow dendrites, spines and axons at different rates, and vary in the degree of pruning. Of particular note is the fact that pyramidal cells in primary visual area (V1) prune more spines than they grow during postnatal development, whereas those in inferotemporal (TEO and TE) and granular prefrontal cortex (gPFC; Brodmann's area 12) grow more than they prune. Moreover, pyramidal cells in TEO, TE and the gPFC continue to grow larger dendritic territories from birth into adulthood, replete with spines, whereas those in V1 become smaller during this time. The developmental profile of intrinsic axons also varies between cortical areas: those in V1, for example, undergo an early proliferation followed by pruning and local consolidation into adulthood, whereas those in area TE tend to establish their territory and consolidate it into adulthood with little pruning. We correlate the anatomical findings with the electrophysiological properties of cells in the different cortical areas, including membrane time constant, depolarizing sag, duration of individual action potentials, and spike-frequency adaptation. All of the electrophysiological variables ramped up before 7 months of age in V1, but continued to ramp up over a protracted period of time in area TE. These data suggest that the anatomical and electrophysiological profiles of pyramidal cells vary among cortical areas at birth, and continue to diverge into adulthood. Moreover, the data reveal that the “use it or lose it” notion of synaptic reinforcement may speak to only part of the story, “use it but you still might lose it” may be just as prevalent in the cerebral cortex.
Collapse
Affiliation(s)
- Guy N Elston
- Centre for Cognitive Neuroscience Sunshine Coast, QLD, Australia
| | - Ichiro Fujita
- Graduate School of Frontier Biosciences and Center for Information and Neural Networks, Osaka University and National Institute of Communication Technology Suita, Japan
| |
Collapse
|
37
|
Butti C, Janeway CM, Townshend C, Wicinski BA, Reidenberg JS, Ridgway SH, Sherwood CC, Hof PR, Jacobs B. The neocortex of cetartiodactyls: I. A comparative Golgi analysis of neuronal morphology in the bottlenose dolphin (Tursiops truncatus), the minke whale (Balaenoptera acutorostrata), and the humpback whale (Megaptera novaeangliae). Brain Struct Funct 2014; 220:3339-68. [PMID: 25100560 DOI: 10.1007/s00429-014-0860-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2014] [Accepted: 07/25/2014] [Indexed: 12/12/2022]
Abstract
The present study documents the morphology of neurons in several regions of the neocortex from the bottlenose dolphin (Tursiops truncatus), the North Atlantic minke whale (Balaenoptera acutorostrata), and the humpback whale (Megaptera novaeangliae). Golgi-stained neurons (n = 210) were analyzed in the frontal and temporal neocortex as well as in the primary visual and primary motor areas. Qualitatively, all three species exhibited a diversity of neuronal morphologies, with spiny neurons including typical pyramidal types, similar to those observed in primates and rodents, as well as other spiny neuron types that had more variable morphology and/or orientation. Five neuron types, with a vertical apical dendrite, approximated the general pyramidal neuron morphology (i.e., typical pyramidal, extraverted, magnopyramidal, multiapical, and bitufted neurons), with a predominance of typical and extraverted pyramidal neurons. In what may represent a cetacean morphological apomorphy, both typical pyramidal and magnopyramidal neurons frequently exhibited a tri-tufted variant. In the humpback whale, there were also large, star-like neurons with no discernable apical dendrite. Aspiny bipolar and multipolar interneurons were morphologically consistent with those reported previously in other mammals. Quantitative analyses showed that neuronal size and dendritic extent increased in association with body size and brain mass (bottlenose dolphin < minke whale < humpback whale). The present data thus suggest that certain spiny neuron morphologies may be apomorphies in the neocortex of cetaceans as compared to other mammals and that neuronal dendritic extent covaries with brain and body size.
Collapse
Affiliation(s)
- Camilla Butti
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, Box 1639, One Gustave L. Levy Place, New York, NY, 10029, USA.
| | - Caroline M Janeway
- Laboratory of Quantitative Neuromorphology, Psychology, Colorado College, 14 E. Cache La Poudre, Colorado Springs, CO, 80903, USA
| | - Courtney Townshend
- Laboratory of Quantitative Neuromorphology, Psychology, Colorado College, 14 E. Cache La Poudre, Colorado Springs, CO, 80903, USA
| | - Bridget A Wicinski
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, Box 1639, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Joy S Reidenberg
- Center for Anatomy and Functional Morphology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Sam H Ridgway
- National Marine Mammal Foundation, 2240 Shelter Island Drive, San Diego, CA, 92106, USA
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, 2110 G Street NW, Washington, DC, 20052, USA
| | - Patrick R Hof
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, Box 1639, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Bob Jacobs
- Laboratory of Quantitative Neuromorphology, Psychology, Colorado College, 14 E. Cache La Poudre, Colorado Springs, CO, 80903, USA
| |
Collapse
|
38
|
Postnatal development of dendritic structure of layer III pyramidal neurons in the medial prefrontal cortex of marmoset. Brain Struct Funct 2014; 220:3245-58. [DOI: 10.1007/s00429-014-0853-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Accepted: 07/16/2014] [Indexed: 11/26/2022]
|
39
|
Teffer K, Buxhoeveden DP, Stimpson CD, Fobbs AJ, Schapiro SJ, Baze WB, McArthur MJ, Hopkins WD, Hof PR, Sherwood CC, Semendeferi K. Developmental changes in the spatial organization of neurons in the neocortex of humans and common chimpanzees. J Comp Neurol 2013; 521:4249-59. [PMID: 23839595 PMCID: PMC4041080 DOI: 10.1002/cne.23412] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2013] [Revised: 05/16/2013] [Accepted: 06/28/2013] [Indexed: 01/01/2023]
Abstract
In adult humans the prefrontal cortex possesses wider minicolumns and more neuropil space than other cortical regions. These aspects of prefrontal cortex architecture, furthermore, are increased in comparison to chimpanzees and other great apes. In order to determine the developmental appearance of this human cortical specialization, we examined the spatial organization of neurons in four cortical regions (frontal pole [Brodmann's area 10], primary motor [area 4], primary somatosensory [area 3b], and prestriate visual cortex [area 18]) in chimpanzees and humans from birth to approximately the time of adolescence (11 years of age). Horizontal spacing distance (HSD) and gray level ratio (GLR) of layer III neurons were measured in Nissl-stained sections. In both human and chimpanzee area 10, HSD was significantly higher in the postweaning specimens compared to the preweaning ones. No significant age-related differences were seen in the other regions in either species. In concert with other recent studies, the current findings suggest that there is a relatively slower maturation of area 10 in both humans and chimpanzees as compared to other cortical regions, and that further refinement of the spatial organization of neurons within this prefrontal area in humans takes place after the postweaning periods included here.
Collapse
Affiliation(s)
- Kate Teffer
- Anthropology Department, University of California, San Diego, 92093
| | | | - Cheryl D. Stimpson
- Anthropology Department, The George Washington University, Washington DC, 20052
| | | | - Steven J. Schapiro
- Department of Veterinary Sciences, The University of Texas M. D. Anderson Cancer Center, Bastrop, TX, 78602
| | - Wallace B. Baze
- Department of Veterinary Sciences, The University of Texas M. D. Anderson Cancer Center, Bastrop, TX, 78602
| | - Mark J. McArthur
- Department of Veterinary Sciences, The University of Texas M. D. Anderson Cancer Center, Bastrop, TX, 78602
| | - William D. Hopkins
- Institute for Neuroscience, Georgia State University, Atlanta, GA, 30303
| | - Patrick R. Hof
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- New York Consortium in Evolutionary Primatology, New York, NY
| | - Chet C. Sherwood
- Anthropology Department, The George Washington University, Washington DC, 20052
| | - Katerina Semendeferi
- Anthropology Department, University of California, San Diego, 92093
- Neuroscience Graduate Program, University of California, San Diego, 92093
| |
Collapse
|
40
|
Aerobic glycolysis in the primate brain: reconsidering the implications for growth and maintenance. Brain Struct Funct 2013; 219:1149-67. [DOI: 10.1007/s00429-013-0662-z] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Accepted: 10/15/2013] [Indexed: 12/15/2022]
|
41
|
Bianchi S, Stimpson CD, Bauernfeind AL, Schapiro SJ, Baze WB, McArthur MJ, Bronson E, Hopkins WD, Semendeferi K, Jacobs B, Hof PR, Sherwood CC. Dendritic morphology of pyramidal neurons in the chimpanzee neocortex: regional specializations and comparison to humans. Cereb Cortex 2013; 23:2429-36. [PMID: 22875862 PMCID: PMC3767963 DOI: 10.1093/cercor/bhs239] [Citation(s) in RCA: 87] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The primate cerebral cortex is characterized by regional variation in the structure of pyramidal neurons, with more complex dendritic arbors and greater spine density observed in prefrontal compared with sensory and motor cortices. Although there are several investigations in humans and other primates, virtually nothing is known about regional variation in the morphology of pyramidal neurons in the cerebral cortex of great apes, humans' closest living relatives. The current study uses the rapid Golgi stain to quantify the dendritic structure of layer III pyramidal neurons in 4 areas of the chimpanzee cerebral cortex: Primary somatosensory (area 3b), primary motor (area 4), prestriate visual (area 18), and prefrontal (area 10) cortex. Consistent with previous studies in humans and macaque monkeys, pyramidal neurons in the prefrontal cortex of chimpanzees exhibit greater dendritic complexity than those in other cortical regions, suggesting that prefrontal cortical evolution in primates is characterized by increased potential for integrative connectivity. Compared with chimpanzees, the pyramidal neurons of humans had significantly longer and more branched dendritic arbors in all cortical regions.
Collapse
Affiliation(s)
- Serena Bianchi
- Department of Anthropology, The George Washington University, Washington, DC
| | - Cheryl D. Stimpson
- Department of Anthropology, The George Washington University, Washington, DC
| | - Amy L. Bauernfeind
- Department of Anthropology, The George Washington University, Washington, DC
| | - Steven J. Schapiro
- Department of Veterinary Sciences, The University of Texas M.D. Anderson Cancer Center, Bastrop, TX 78602
| | - Wallace B. Baze
- Department of Veterinary Sciences, The University of Texas M.D. Anderson Cancer Center, Bastrop, TX 78602
| | - Mark J. McArthur
- Department of Veterinary Sciences, The University of Texas M.D. Anderson Cancer Center, Bastrop, TX 78602
| | | | - William D. Hopkins
- Neuroscience Institute, Georgia State University, Atlanta, Georgia 30302
- Division of Developmental and Cognitive Neuroscience, Yerkes National Primate Research Center, Atlanta, GA 30322
| | - Katerina Semendeferi
- Department of Anthropology and Neuroscience Graduate Program, University of California, San Diego, La Jolla, CA 92093
| | - Bob Jacobs
- Department of Psychology, Colorado College, Colorado Springs, CO 80903
| | - Patrick R. Hof
- Fishberg Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, NY 10029 and
- New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - Chet C. Sherwood
- Department of Anthropology, The George Washington University, Washington, DC
| |
Collapse
|
42
|
Synaptogenesis and development of pyramidal neuron dendritic morphology in the chimpanzee neocortex resembles humans. Proc Natl Acad Sci U S A 2013; 110 Suppl 2:10395-401. [PMID: 23754422 DOI: 10.1073/pnas.1301224110] [Citation(s) in RCA: 92] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Neocortical development in humans is characterized by an extended period of synaptic proliferation that peaks in mid-childhood, with subsequent pruning through early adulthood, as well as relatively delayed maturation of neuronal arborization in the prefrontal cortex compared with sensorimotor areas. In macaque monkeys, cortical synaptogenesis peaks during early infancy and developmental changes in synapse density and dendritic spines occur synchronously across cortical regions. Thus, relatively prolonged synapse and neuronal maturation in humans might contribute to enhancement of social learning during development and transmission of cultural practices, including language. However, because macaques, which share a last common ancestor with humans ≈ 25 million years ago, have served as the predominant comparative primate model in neurodevelopmental research, the paucity of data from more closely related great apes leaves unresolved when these evolutionary changes in the timing of cortical development became established in the human lineage. To address this question, we used immunohistochemistry, electron microscopy, and Golgi staining to characterize synaptic density and dendritic morphology of pyramidal neurons in primary somatosensory (area 3b), primary motor (area 4), prestriate visual (area 18), and prefrontal (area 10) cortices of developing chimpanzees (Pan troglodytes). We found that synaptogenesis occurs synchronously across cortical areas, with a peak of synapse density during the juvenile period (3-5 y). Moreover, similar to findings in humans, dendrites of prefrontal pyramidal neurons developed later than sensorimotor areas. These results suggest that evolutionary changes to neocortical development promoting greater neuronal plasticity early in postnatal life preceded the divergence of the human and chimpanzee lineages.
Collapse
|
43
|
Abstract
Cortical maturation was studied in 65 infants between 27 and 46 wk postconception using structural and diffusion magnetic resonance imaging. Alterations in neural structure and complexity were inferred from changes in mean diffusivity and fractional anisotropy, analyzed by sampling regions of interest and also by a unique whole-cortex mapping approach. Mean diffusivity was higher in gyri than sulci and in frontal compared with occipital lobes, decreasing consistently throughout the study period. Fractional anisotropy declined until 38 wk, with initial values and rates of change higher in gyri, frontal and temporal poles, and parietal cortex; and lower in sulcal, perirolandic, and medial occipital cortex. Neuroanatomical studies and experimental diffusion-anatomic correlations strongly suggested the interpretation that cellular and synaptic complexity and density increased steadily throughout the period, whereas elongation and branching of dendrites orthogonal to cortical columns was later and faster in higher-order association cortex, proceeding rapidly before becoming undetectable after 38 wk. The rate of microstructural maturation correlated locally with cortical growth, and predicted higher neurodevelopmental test scores at 2 y of age. Cortical microstructural development was reduced in a dose-dependent fashion by longer premature exposure to the extrauterine environment, and preterm infants at term-corrected age possessed less mature cortex than term-born infants. The results are compatible with predictions of the tension theory of cortical growth and show that rapidly developing cortical microstructure is vulnerable to the effects of premature birth, suggesting a mechanism for the adverse effects of preterm delivery on cognitive function.
Collapse
|
44
|
Hansen MB, Jespersen SN, Leigland LA, Kroenke CD. Using diffusion anisotropy to characterize neuronal morphology in gray matter: the orientation distribution of axons and dendrites in the NeuroMorpho.org database. Front Integr Neurosci 2013; 7:31. [PMID: 23675327 PMCID: PMC3653140 DOI: 10.3389/fnint.2013.00031] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2012] [Accepted: 04/16/2013] [Indexed: 01/07/2023] Open
Abstract
Accurate mathematical modeling is integral to the ability to interpret diffusion magnetic resonance (MR) imaging data in terms of cellular structure in brain gray matter (GM). In previous work, we derived expressions to facilitate the determination of the orientation distribution of axonal and dendritic processes from diffusion MR data. Here we utilize neuron reconstructions available in the NeuroMorpho database (www.neuromorpho.org) to assess the validity of the model we proposed by comparing morphological properties of the neurons to predictions based on diffusion MR simulations using the reconstructed neuron models. Initially, the method for directly determining neurite orientation distributions is shown to not depend on the line length used to quantify cylindrical elements. Further variability in neuron morphology is characterized relative to neuron type, species, and laboratory of origin. Subsequently, diffusion MR signals are simulated based on human neocortical neuron reconstructions. This reveals a bias in which diffusion MR data predict neuron orientation distributions to have artificially low anisotropy. This bias is shown to arise from shortcomings (already at relatively low diffusion weighting) in the Gaussian approximation of diffusion, in the presence of restrictive barriers, and data analysis methods involving higher moments of the cumulant expansion are shown to be capable of reducing the magnitude of the observed bias.
Collapse
Affiliation(s)
- Mikkel B Hansen
- Center for Functionally Integrative Neuroscience and MINDLab, NeuroCampus Aarhus, Aarhus University Aarhus, Denmark
| | | | | | | |
Collapse
|
45
|
Travis KE, Curran MM, Torres C, Leonard MK, Brown TT, Dale AM, Elman JL, Halgren E. Age-related changes in tissue signal properties within cortical areas important for word understanding in 12- to 19-month-old infants. ACTA ACUST UNITED AC 2013; 24:1948-55. [PMID: 23448869 DOI: 10.1093/cercor/bht052] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Recently, our laboratory has shown that the neural mechanisms for encoding lexico-semantic information in adults operate functionally by 12-18 months of age within left frontotemporal cortices (Travis et al., 2011. Spatiotemporal neural dynamics of word understanding in 12- to 18-month-old-infants. Cereb Cortex. 8:1832-1839). However, there is minimal knowledge of the structural changes that occur within these and other cortical regions important for language development. To identify regional structural changes taking place during this important period in infant development, we examined age-related changes in tissue signal properties of gray matter (GM) and white matter (WM) intensity and contrast. T1-weighted surface-based measures were acquired from 12- to 19-month-old infants and analyzed using a general linear model. Significant age effects were observed for GM and WM intensity and contrast within bilateral inferior lateral and anterovental temporal regions, dorsomedial frontal, and superior parietal cortices. Region of interest (ROI) analyses revealed that GM and WM intensity and contrast significantly increased with age within the same left lateral temporal regions shown to generate lexico-semantic activity in infants and adults. These findings suggest that neurophysiological processes supporting linguistic and cognitive behaviors may develop before cellular and structural maturation is complete within associative cortices. These results have important implications for understanding the neurobiological mechanisms relating structural to functional brain development.
Collapse
Affiliation(s)
| | | | | | | | | | - Anders M Dale
- Department of Radiology, Multimodal Imaging Laboratory, Department of Neurosciences
| | - Jeffrey L Elman
- Kavli Institute for Brain and Mind, and Department of Cognitive Science, University of California, San Diego, CA, USA
| | - Eric Halgren
- Department of Radiology, Multimodal Imaging Laboratory, Kavli Institute for Brain and Mind, and
| |
Collapse
|
46
|
Spocter MA, Hopkins WD, Barks SK, Bianchi S, Hehmeyer AE, Anderson SM, Stimpson CD, Fobbs AJ, Hof PR, Sherwood CC. Neuropil distribution in the cerebral cortex differs between humans and chimpanzees. J Comp Neurol 2012; 520:2917-29. [PMID: 22350926 DOI: 10.1002/cne.23074] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Increased connectivity of high-order association regions in the neocortex has been proposed as a defining feature of human brain evolution. At present, however, there are limited comparative data to examine this claim fully. We tested the hypothesis that the distribution of neuropil across areas of the neocortex of humans differs from that of one of our closest living relatives, the common chimpanzee. The neuropil provides a proxy measure of total connectivity within a local region because it is composed mostly of dendrites, axons, and synapses. Using image analysis techniques, we quantified the neuropil fraction from both hemispheres in six cytoarchitectonically defined regions including frontopolar cortex (area 10), Broca's area (area 45), frontoinsular cortex (area FI), primary motor cortex (area 4), primary auditory cortex (area 41/42), and the planum temporale (area 22). Our results demonstrate that humans exhibit a unique distribution of neuropil in the neocortex compared to chimpanzees. In particular, the human frontopolar cortex and the frontoinsular cortex had a significantly higher neuropil fraction than the other areas. In chimpanzees these prefrontal regions did not display significantly more neuropil, but the primary auditory cortex had a lower neuropil fraction than other areas. Our results support the conclusion that enhanced connectivity in the prefrontal cortex accompanied the evolution of the human brain. These species differences in neuropil distribution may offer insight into the neural basis of human cognition, reflecting enhancement of the integrative capacity of the prefrontal cortex.
Collapse
Affiliation(s)
- Muhammad A Spocter
- Department of Anthropology, The George Washington University, Washington, DC 20052, USA
| | | | | | | | | | | | | | | | | | | |
Collapse
|
47
|
Abstract
Nerve myelination facilitates saltatory action potential conduction and exhibits spatiotemporal variation during development associated with the acquisition of behavioral and cognitive maturity. Although human cognitive development is unique, it is not known whether the ontogenetic progression of myelination in the human neocortex is evolutionarily exceptional. In this study, we quantified myelinated axon fiber length density and the expression of myelin-related proteins throughout postnatal life in the somatosensory (areas 3b/3a/1/2), motor (area 4), frontopolar (prefrontal area 10), and visual (areas 17/18) neocortex of chimpanzees (N = 20) and humans (N = 33). Our examination revealed that neocortical myelination is developmentally protracted in humans compared with chimpanzees. In chimpanzees, the density of myelinated axons increased steadily until adult-like levels were achieved at approximately the time of sexual maturity. In contrast, humans displayed slower myelination during childhood, characterized by a delayed period of maturation that extended beyond late adolescence. This comparative research contributes evidence crucial to understanding the evolution of human cognition and behavior, which arises from the unfolding of nervous system development within the context of an enriched cultural environment. Perturbations of normal developmental processes and the decreased expression of myelin-related molecules have been related to psychiatric disorders such as schizophrenia. Thus, these species differences suggest that the human-specific shift in the timing of cortical maturation during adolescence may have implications for vulnerability to certain psychiatric disorders.
Collapse
|
48
|
Khundrakpam BS, Reid A, Brauer J, Carbonell F, Lewis J, Ameis S, Karama S, Lee J, Chen Z, Das S, Evans AC. Developmental changes in organization of structural brain networks. ACTA ACUST UNITED AC 2012; 23:2072-85. [PMID: 22784607 DOI: 10.1093/cercor/bhs187] [Citation(s) in RCA: 158] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.
Collapse
Affiliation(s)
- Budhachandra S Khundrakpam
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
49
|
Orlowski D, Bjarkam CR. A simple reproducible and time saving method of semi-automatic dendrite spine density estimation compared to manual spine counting. J Neurosci Methods 2012; 208:128-33. [DOI: 10.1016/j.jneumeth.2012.05.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2012] [Revised: 04/27/2012] [Accepted: 05/08/2012] [Indexed: 10/28/2022]
|
50
|
|