1
|
Lee S, Song Y, Hong H, Joo Y, Ha E, Shim Y, Hong SN, Kim J, Lyoo IK, Yoon S, Kim DW. Changes in Structural Covariance among Olfactory-related Brain Regions in Anosmia Patients. Exp Neurobiol 2024; 33:99-106. [PMID: 38724479 PMCID: PMC11089402 DOI: 10.5607/en24007] [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: 03/11/2024] [Revised: 04/01/2024] [Accepted: 04/09/2024] [Indexed: 05/15/2024] Open
Abstract
Anosmia, characterized by the loss of smell, is associated not only with dysfunction in the peripheral olfactory system but also with changes in several brain regions involved in olfactory processing. Specifically, the orbitofrontal cortex is recognized for its pivotal role in integrating olfactory information, engaging in bidirectional communication with the primary olfactory regions, including the olfactory cortex, amygdala, and entorhinal cortex. However, little is known about alterations in structural connections among these brain regions in patients with anosmia. In this study, high-resolution T1-weighted images were obtained from participants. Utilizing the volumes of key brain regions implicated in olfactory function, we employed a structural covariance approach to investigate brain reorganization patterns in patients with anosmia (n=22) compared to healthy individuals (n=30). Our structural covariance analysis demonstrated diminished connectivity between the amygdala and entorhinal cortex, components of the primary olfactory network, in patients with anosmia compared to healthy individuals (z=-2.22, FDR-corrected p=0.039). Conversely, connectivity between the orbitofrontal cortex-a major region in the extended olfactory network-and amygdala was found to be enhanced in the anosmia group compared to healthy individuals (z=2.32, FDR-corrected p=0.039). However, the structural connections between the orbitofrontal cortex and entorhinal cortex did not differ significantly between the groups (z=0.04, FDR-corrected p=0.968). These findings suggest a potential structural reorganization, particularly of higher-order cortical regions, possibly as a compensatory effort to interpret the limited olfactory information available in individuals with olfactory loss.
Collapse
Affiliation(s)
- Suji Lee
- College of Pharmacy, Dongduk Women’s University, Seoul 02748, Korea
| | - Yumi Song
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul 03760, Korea
| | - Haejin Hong
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
| | - Yoonji Joo
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
| | - Eunji Ha
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
| | - Youngeun Shim
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul 03760, Korea
| | - Seung-No Hong
- Department of Otorhinolaryngology-Head & Neck Surgery, Boramae Medical Center, Seoul National University College of Medicine, Seoul 07061, Korea
| | - Jungyoon Kim
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul 03760, Korea
| | - In Kyoon Lyoo
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul 03760, Korea
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea
| | - Sujung Yoon
- Ewha Brain Institute, Ewha Womans University, Seoul 03760, Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul 03760, Korea
| | - Dae Woo Kim
- Department of Otorhinolaryngology-Head & Neck Surgery, Boramae Medical Center, Seoul National University College of Medicine, Seoul 07061, Korea
| |
Collapse
|
2
|
Pulli EP, Nolvi S, Eskola E, Nordenswan E, Holmberg E, Copeland A, Kumpulainen V, Silver E, Merisaari H, Saunavaara J, Parkkola R, Lähdesmäki T, Saukko E, Kataja E, Korja R, Karlsson L, Karlsson H, Tuulari JJ. Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study. Hum Brain Mapp 2023; 44:5582-5601. [PMID: 37606608 PMCID: PMC10619410 DOI: 10.1002/hbm.26463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/23/2023] Open
Abstract
Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.
Collapse
Affiliation(s)
- Elmo P. Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Turku Institute for Advanced Studies, Department of Psychology and Speech‐Language PathologyUniversity of TurkuTurkuFinland
| | - Eeva Eskola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychologyUniversity of TurkuTurkuFinland
| | - Elisabeth Nordenswan
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Eeva Holmberg
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of RadiologyUniversity of TurkuTurkuFinland
| | - Jani Saunavaara
- Department of Medical PhysicsTurku University Hospital and University of TurkuTurkuFinland
| | - Riitta Parkkola
- Department of RadiologyUniversity of TurkuTurkuFinland
- Department of RadiologyTurku University HospitalTurkuFinland
| | - Tuire Lähdesmäki
- Pediatric Neurology, Department of Pediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
| | | | - Eeva‐Leena Kataja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychologyUniversity of TurkuTurkuFinland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of Pediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
- Turku Collegium for Science, Medicine and TechnologyUniversity of TurkuTurkuFinland
- Department of PsychiatryUniversity of OxfordOxfordUK
| |
Collapse
|
3
|
Lan H, Suo X, Zuo C, Pan N, Zhang X, Kemp GJ, Gong Q, Wang S. Distinct pre-COVID brain structural signatures in COVID-19-related post-traumatic stress symptoms and post-traumatic growth. Cereb Cortex 2023; 33:11373-11383. [PMID: 37804248 DOI: 10.1093/cercor/bhad372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 10/09/2023] Open
Abstract
Post-traumatic stress symptoms and post-traumatic growth are common co-occurring psychological responses following exposure to traumatic events (such as COVID-19 pandemic), their mutual relationship remains unclear. To explore this relationship, structural magnetic resonance imaging data were acquired from 115 general college students before the COVID-19 pandemic, and follow-up post-traumatic stress symptoms and post-traumatic growth measurements were collected during the pandemic. Voxel-based morphometry was conducted and individual structural covariance networks based on gray matter volume were further analyzed using graph theory and partial least squares correlation. Behavioral correlation found no significant relationship between post-traumatic stress symptoms and post-traumatic growth. Voxel-based morphometry analyses showed that post-traumatic stress symptoms were positively correlated with gray matter volume in medial prefrontal cortex/dorsal anterior cingulate cortex, and post-traumatic growth was negatively correlated with gray matter volume in left dorsolateral prefrontal cortex. Structural covariance network analyses found that post-traumatic stress symptoms were negatively correlated with the local efficiency and clustering coefficient of the network. Moreover, partial least squares correlation showed that post-traumatic stress symptoms were correlated with pronounced nodal properties patterns in default mode, sensory and motor regions, and a marginal correlation of post-traumatic growth with a nodal property pattern in emotion regulation-related regions. This study advances our understanding of the neurobiological substrates of post-traumatic stress symptoms and post-traumatic growth, and suggests that they may have different neuroanatomical features.
Collapse
Affiliation(s)
- Huan Lan
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Xueling Suo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Chao Zuo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Nanfang Pan
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Xun Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3BX, United Kingdom
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen 361000, China
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| |
Collapse
|
4
|
Urbanik A, Guz W, Gołębiowski M, Szurowska E, Majos A, Sąsiadek M, Stajgis M, Ostrogórska M. Assessment of the corpus callosum size in male individuals with high intelligence quotient (members of Mensa International). RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:49-54. [PMID: 37160478 PMCID: PMC10689507 DOI: 10.1007/s00117-023-01146-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/27/2023] [Indexed: 05/11/2023]
Abstract
OBJECTIVES The aim of this study was to assess the size of the corpus callosum in members of Mensa International, which is the world's largest and oldest high-intelligence quotient (IQ) society. METHODS We performed T2-weighted magnetic resonance imaging (Repetition Time, TR = 3200 ms, Time of Echo, TE = 409 ms) to examine the brain of members of Mensa International (Polish national group) in order to assess the size of the corpus callosum. Results from 113 male MENSA members and 96 controls in the age range of 21-40 years were analyzed. RESULTS The comparative analysis showed that the mean length of the corpus callosum and the thickness of the isthmus were significantly greater in the Mensa members compared to the control groups. A statistically significant difference was also identified in the largest linear dimension of the brain from the frontal lobe to the occipital lobe. The mean corpus callosum cross-sectional area and its ratio to the brain area were significantly greater in the Mensa members. CONCLUSIONS The results show that the dimensions (linear measures and midsagittal cross-sectional surface area) of the corpus callosum were significantly greater in the group of Mensa members than in the controls.
Collapse
Affiliation(s)
- Andrzej Urbanik
- Department of Radiology, Collegium Medicum, Jagiellonian University, Kopernika 19, 31-501, Krakow, Poland
| | - Wiesław Guz
- Department of Electroradiology, University of Rzeszów, Rzeszów, Poland
| | - Marek Gołębiowski
- I-st Department of Clinical Radiology, Medical University of Warsaw, Warszawa, Poland
| | - Edyta Szurowska
- 2nd Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
| | - Agata Majos
- Chair of Radiology and Imaging Diagnostics, Medical University of Łódź, Łódź, Poland
| | - Marek Sąsiadek
- Department of Radiology, Wroclaw Medical University, Wrocław, Poland
| | - Marek Stajgis
- Department of General Radiology and Neuroradiology, Poznan University of Medical Sciences, Poznań, Poland
| | - Monika Ostrogórska
- Department of Radiology, Collegium Medicum, Jagiellonian University, Kopernika 19, 31-501, Krakow, Poland.
| |
Collapse
|
5
|
Woodfield J, Chin RFM, van Schooneveld MMJ, van den Heuvel M, Bastin ME, Braun KPJ. The association of structural connectome efficiency with cognition in children with epilepsy. Epilepsy Behav 2023; 148:109462. [PMID: 37844437 DOI: 10.1016/j.yebeh.2023.109462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/21/2023] [Accepted: 09/26/2023] [Indexed: 10/18/2023]
Abstract
OBJECTIVE Cognitive impairment is common in children with epilepsy (CWE), but understanding the underlying pathological processes is challenging. We aimed to investigate the association of structural brain network organisation with cognition. METHODS This was a retrospective cohort study of CWE without structural brain abnormalities, comparing whole brain network characteristics between those with cognitive impairment and those with intact cognition. We created structural whole-brain connectomes from anatomical and diffusion tensor magnetic resonance imaging using the number of streamlines and tract-averaged fractional anisotropy. We assessed the differences in average path length and global network efficiency between children with cognitive impairment and those without,using multivariable analyses to account for possible clinical group differences. RESULTS Twenty-eight CWE and cognitive impairment had lower whole brain network global efficiency compared with 34 children with intact cognition (0.54, standard deviation (SD):0.003 vs. 0.56, SD:0.002, p < 0.001), which is equivalent to longer normalized network average path lengths (1.14, SD:0.05 vs. 1.10, SD:0.02, p = 0.003). In multivariable logistic regression cognitive impairment was not significantly associated with age of onset, duration of epilepsy, or number of antiseizure medications, but was independently associated with daily seizures (p = 0.04) and normalized average path length (p = 0.007). CONCLUSIONS Higher structural network average path length and lower global network efficiency may be imaging biomarkers of cognitive impairment in epilepsy. Understanding what leads to changes in structural connectivity could aid identification of modifiable risk factors for cognitive impairment. These findings are only applicable to the specific cohort studied, and further confirmation in other cohorts is required.
Collapse
Affiliation(s)
- Julie Woodfield
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Department of Clinical Neurosciences, NHS Lothian, Edinburgh, United Kingdom; Muir Maxwell Epilepsy Centre, University of Edinburgh, Edinburgh, United Kingdom.
| | - Richard F M Chin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Muir Maxwell Epilepsy Centre, University of Edinburgh, Edinburgh, United Kingdom; Royal Hospital for Children and Young People, NHS Lothian, Edinburgh, United Kingdom
| | | | - Martijn van den Heuvel
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Kees P J Braun
- Department of Paediatric Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
| |
Collapse
|
6
|
Sokol DK, Lahiri DK. Neurodevelopmental disorders and microcephaly: how apoptosis, the cell cycle, tau and amyloid-β precursor protein APPly. Front Mol Neurosci 2023; 16:1201723. [PMID: 37808474 PMCID: PMC10556256 DOI: 10.3389/fnmol.2023.1201723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 08/08/2023] [Indexed: 10/10/2023] Open
Abstract
Recent studies promote new interest in the intersectionality between autism spectrum disorder (ASD) and Alzheimer's Disease. We have reported high levels of Amyloid-β Precursor Protein (APP) and secreted APP-alpha (sAPPa ) and low levels of amyloid-beta (Aβ) peptides 1-40 and 1-42 (Aβ40, Aβ42) in plasma and brain tissue from children with ASD. A higher incidence of microcephaly (head circumference less than the 3rd percentile) associates with ASD compared to head size in individuals with typical development. The role of Aβ peptides as contributors to acquired microcephaly in ASD is proposed. Aβ may lead to microcephaly via disruption of neurogenesis, elongation of the G1/S cell cycle, and arrested cell cycle promoting apoptosis. As the APP gene exists on Chromosome 21, excess Aβ peptides occur in Trisomy 21-T21 (Down's Syndrome). Microcephaly and some forms of ASD associate with T21, and therefore potential mechanisms underlying these associations will be examined in this review. Aβ peptides' role in other neurodevelopmental disorders that feature ASD and acquired microcephaly are reviewed, including dup 15q11.2-q13, Angelman and Rett syndrome.
Collapse
Affiliation(s)
- Deborah K. Sokol
- Section of Pediatrics, Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Debomoy K. Lahiri
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| |
Collapse
|
7
|
Li X, Hao H, Li Y, Au LWC, Du G, Gao X, Yan J, Tong RKY, Lou W. Menstrually-related migraine shapes the structural similarity network integration of brain. Cereb Cortex 2023; 33:9867-9876. [PMID: 37415071 DOI: 10.1093/cercor/bhad250] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 06/18/2023] [Accepted: 06/19/2023] [Indexed: 07/08/2023] Open
Abstract
Menstrually-related migraine (MM) is a primary migraine in women of reproductive age. The underlying neural mechanism of MM was still unclear. In this study, we aimed to reveal the case-control differences in network integration and segregation for the morphometric similarity network of MM. Thirty-six patients with MM and 29 healthy females were recruited and underwent MRI scanning. The morphometric features were extracted in each region to construct the single-subject interareal cortical connection using morphometric similarity. The network topology characteristics, in terms of integration and segregation, were analyzed. Our results revealed that, in the absence of morphology differences, disrupted cortical network integration was found in MM patients compared to controls. The patients with MM showed a decreased global efficiency and increased characteristic path length compared to healthy controls. Regional efficiency analysis revealed the decreased efficiency in the left precentral gyrus and bilateral superior temporal gyrus contributed to the decreased network integration. The increased nodal degree centrality in the right pars triangularis was positively associated with the attack frequency in MM. Our results suggested MM would reorganize the morphology in the pain-related brain regions and reduce the parallel information processing capacity of the brain.
Collapse
Affiliation(s)
- Xinyu Li
- Imaging Center, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China
| | - Huifen Hao
- Imaging Center, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China
| | - Yingying Li
- Imaging Center, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China
| | - Lisa Wing-Chi Au
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Ganqin Du
- Department of Neurology, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China
| | - Xiuju Gao
- Department of Neurology, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China
| | - Junqiang Yan
- Department of Neurology, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China
| | - Raymond Kai-Yu Tong
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Wutao Lou
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
8
|
Zhu Y, Gong W, Lu X, Wang H. Effective connectivity analysis of brain networks of mathematically gifted adolescents using transfer entropy. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023. [DOI: 10.3233/jifs-223819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Using functional neuroimaging, electrophysiological techniques and neural data processing techniques, neuroscientists have found that mathematically gifted adolescents exhibit unusual neurocognitive features in the activation of task-related brain regions. Hemispheric information interaction, functional reorganization of networks, and utilization of task-related brain regions are beneficial to rapid and efficient task processing. Based on Granger causality channel selection, the transfer entropy (TE) value between effective channels was computed, and the information flow patterns in the directed functional brain networks derived from electroencephalography (EEG) data during deductive reasoning tasks were explored. We evaluated the workspace configuration patterns of the brain network and the global integration characteristics of separated brain regions using node strength, motif, directed clustering coefficient and characteristic path length in the brain networks of mathematically gifted adolescents with effective connectivity. The empirical results demonstrated that a more integrated functional network at the global level and a more efficient clique at the local level support a pattern of workspace configuration in the mathematically gifted brain that is more conducive to task-related information processing.
Collapse
|
9
|
A critical role of brain network architecture in a continuum model of autism spectrum disorders spanning from healthy individuals with genetic liability to individuals with ASD. Mol Psychiatry 2023; 28:1210-1218. [PMID: 36575304 PMCID: PMC10005951 DOI: 10.1038/s41380-022-01916-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/21/2022] [Accepted: 12/09/2022] [Indexed: 12/28/2022]
Abstract
Studies have shown cortical alterations in individuals with autism spectrum disorders (ASD) as well as in individuals with high polygenic risk for ASD. An important addition to the study of altered cortical anatomy is the investigation of the underlying brain network architecture that may reveal brain-wide mechanisms in ASD and in polygenic risk for ASD. Such an approach has been proven useful in other psychiatric disorders by revealing that brain network architecture shapes (to an extent) the disorder-related cortical alterations. This study uses data from a clinical dataset-560 male subjects (266 individuals with ASD and 294 healthy individuals, CTL, mean age at 17.2 years) from the Autism Brain Imaging Data Exchange database, and data of 391 healthy individuals (207 males, mean age at 12.1 years) from the Pediatric Imaging, Neurocognition and Genetics database. ASD-related cortical alterations (group difference, ASD-CTL, in cortical thickness) and cortical correlates of polygenic risk for ASD were assessed, and then statistically compared with structural connectome-based network measures (such as hubs) using spin permutation tests. Next, we investigated whether polygenic risk for ASD could be predicted by network architecture by building machine-learning based prediction models, and whether the top predictors of the model were identified as disease epicenters of ASD. We observed that ASD-related cortical alterations as well as cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. We also observed that age progression of ASD-related cortical alterations and cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. Further investigation revealed that structural connectomes predicted polygenic risk for ASD (r = 0.30, p < 0.0001), and two brain regions (the left inferior parietal and left suparmarginal) with top predictive connections were identified as disease epicenters of ASD. Our study highlights a critical role of network architecture in a continuum model of ASD spanning from healthy individuals with genetic risk to individuals with ASD. Our study also highlights the strength of investigating polygenic risk scores in addition to multi-modal neuroimaging measures to better understand the interplay between genetic risk and brain alterations associated with ASD.
Collapse
|
10
|
Zhou Y, Müller HG, Zhu C, Chen Y, Wang JL, O'Muircheartaigh J, Bruchhage M, Deoni S, Bruchhage M, Carnell S, Deoni S, D’Sa V, Huentelman M, Klepac-Ceraj V, LeBourgeois M, Müller HG, O’Muircheartaigh J, Wang JL. Network evolution of regional brain volumes in young children reflects neurocognitive scores and mother's education. Sci Rep 2023; 13:2984. [PMID: 36804963 PMCID: PMC9941570 DOI: 10.1038/s41598-023-29797-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 02/10/2023] [Indexed: 02/22/2023] Open
Abstract
The maturation of regional brain volumes from birth to preadolescence is a critical developmental process that underlies emerging brain structural connectivity and function. Regulated by genes and environment, the coordinated growth of different brain regions plays an important role in cognitive development. Current knowledge about structural network evolution is limited, partly due to the sparse and irregular nature of most longitudinal neuroimaging data. In particular, it is unknown how factors such as mother's education or sex of the child impact the structural network evolution. To address this issue, we propose a method to construct evolving structural networks and study how the evolving connections among brain regions as reflected at the network level are related to maternal education and biological sex of the child and also how they are associated with cognitive development. Our methodology is based on applying local Fréchet regression to longitudinal neuroimaging data acquired from the RESONANCE cohort, a cohort of healthy children (245 females and 309 males) ranging in age from 9 weeks to 10 years. Our findings reveal that sustained highly coordinated volume growth across brain regions is associated with lower maternal education and lower cognitive development. This suggests that higher neurocognitive performance levels in children are associated with increased variability of regional growth patterns as children age.
Collapse
Affiliation(s)
- Yidong Zhou
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA.
| | - Hans-Georg Müller
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Changbo Zhu
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Yaqing Chen
- Department of Statistics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Jane-Ling Wang
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Muriel Bruchhage
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, USA.,Department of Diagnostic Imaging, Rhode Island Hospital, Providence, USA.,Institute of Social Sciences, Stavanger University, Stavanger, 4021, Norway
| | - Sean Deoni
- Maternal, Newborn, and Child Health Discovery and Tools, Bill and Melinda Gates Foundation, Seattle, WA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
11
|
Thijssen S, Riem MME, Vijayakumar N, Cima MJ, Whittle S. Editorial: Nurturing the brain: Associations between family environment and child brain development. Front Neurosci 2023; 17:1119838. [PMID: 36798461 PMCID: PMC9927639 DOI: 10.3389/fnins.2023.1119838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 01/16/2023] [Indexed: 02/01/2023] Open
Affiliation(s)
- Sandra Thijssen
- Behavioral Science Institute, Radboud University, Nijmegen, Netherlands,*Correspondence: Sandra Thijssen ✉
| | | | | | - Maaike J. Cima
- Behavioral Science Institute, Radboud University, Nijmegen, Netherlands,VIGO, Child and Youth Care Institute, Nijmegen, Netherlands
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre (MNC), Department of Psychiatry, The University of Melbourne & Melbourne Health, Melbourne, VIC, Australia
| |
Collapse
|
12
|
Richmond S, Beare R, Johnson KA, Bray K, Pozzi E, Allen NB, Seal ML, Whittle S. Maternal warmth is associated with network segregation across late childhood: A longitudinal neuroimaging study. Front Psychol 2022; 13:917189. [PMID: 36176802 PMCID: PMC9514138 DOI: 10.3389/fpsyg.2022.917189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 08/22/2022] [Indexed: 12/02/2022] Open
Abstract
The negative impact of adverse experiences in childhood on neurodevelopment is well documented. Less attention however has been given to the impact of variations in “normative” parenting behaviors. The influence of these parenting behaviors is likely to be marked during periods of rapid brain reorganization, such as late childhood. The aim of the current study was to investigate associations between normative parenting behaviors and the development of structural brain networks across late childhood. Data were collected from a longitudinal sample of 114 mother-child dyads (54% female children, M age 8.41 years, SD = 0.32 years), recruited from low socioeconomic areas of Melbourne, Australia. At the first assessment parenting behaviors were coded from two lab-based interaction tasks and structural magnetic resonance imaging (MRI) scans of the children were performed. At the second assessment, approximately 18 months later (M age 9.97 years, SD = 0.37 years) MRI scans were repeated. Cortical thickness (CT) was extracted from T1-weighted images using FreeSurfer. Structural covariance (SC) networks were constructed from partial correlations of CT estimates between brain regions and estimates of network efficiency and modularity were obtained for each time point. The change in these network measures, from Time 1 to Time 2, was also calculated. At Time 2, less positive maternal affective behavior was associated with higher modularity (more segregated networks), while negative maternal affective behavior was not related. No support was found for an association between local or global efficacy and maternal affective behaviors at Time 2. Similarly, no support was demonstrated for associations between maternal affective behaviors and change in network efficiency and modularity, from Time 1 to Time 2. These results indicate that normative variations in parenting may influence the development of structural brain networks in late childhood and extend current knowledge about environmental influences on structural connectivity in a developmental context.
Collapse
Affiliation(s)
- Sally Richmond
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
- *Correspondence: Sally Richmond,
| | - Richard Beare
- Developmental Imaging, Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | - Katherine A. Johnson
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Katherine Bray
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Elena Pozzi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
| | - Nicholas B. Allen
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia
- Department of Psychology, University of Oregon, Eugene, OR, United States
| | - Marc L. Seal
- Developmental Imaging, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Department of Pediatrics, The University of Melbourne, Parkville, VIC, Australia
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
| |
Collapse
|
13
|
Bolton TAW, Van De Ville D, Régis J, Witjas T, Girard N, Levivier M, Tuleasca C. Morphometric features of drug-resistant essential tremor and recovery after stereotactic radiosurgical thalamotomy. Netw Neurosci 2022; 6:850-869. [PMID: 36605417 PMCID: PMC9810368 DOI: 10.1162/netn_a_00253] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/02/2022] [Indexed: 01/09/2023] Open
Abstract
Essential tremor (ET) is the most common movement disorder. Its neural underpinnings remain unclear. Here, we quantified structural covariance between cortical thickness (CT), surface area (SA), and mean curvature (MC) estimates in patients with ET before and 1 year after ventro-intermediate nucleus stereotactic radiosurgical thalamotomy, and contrasted the observed patterns with those from matched healthy controls. For SA, complex rearrangements within a network of motion-related brain areas characterized patients with ET. This was complemented by MC alterations revolving around the left middle temporal cortex and the disappearance of positive-valued covariance across both modalities in the right fusiform gyrus. Recovery following thalamotomy involved MC readjustments in frontal brain centers, the amygdala, and the insula, capturing nonmotor characteristics of the disease. The appearance of negative-valued CT covariance between the left parahippocampal gyrus and hippocampus was another recovery mechanism involving high-level visual areas. This was complemented by the appearance of negative-valued CT/MC covariance, and positive-valued SA/MC covariance, in the right inferior temporal cortex and bilateral fusiform gyrus. Our results demonstrate that different morphometric properties provide complementary information to understand ET, and that their statistical cross-dependences are also valuable. They pinpoint several anatomical features of the disease and highlight routes of recovery following thalamotomy.
Collapse
Affiliation(s)
- Thomas A. W. Bolton
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland,Connectomics Laboratory, Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland,* Corresponding Author:
| | - Dimitri Van De Ville
- Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Jean Régis
- Stereotactic and Functional Neurosurgery Service and Gamma Knife Unit, Assistance Publique-Hôpitaux de Marseille, Centre Hospitalier Universitaire de la Timone, Marseille, France
| | - Tatiana Witjas
- Neurology Department, Assistance Publique-Hôpitaux de Marseille, Centre Hospitalier Universitaire de la Timone, Marseille, France
| | - Nadine Girard
- Department of Diagnostic and Interventional Neuroradiology, Centre de Résonance Magnétique Biologique et Médicale, Assistance Publique-Hôpitaux de Marseille, Centre Hospitalier Universitaire de la Timone, Marseille, France
| | - Marc Levivier
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland,Faculty of Biology and Medicine (FBM), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Constantin Tuleasca
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland,Faculty of Biology and Medicine (FBM), University of Lausanne (UNIL), Lausanne, Switzerland,Signal Processing Laboratory (LTS 5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| |
Collapse
|
14
|
Bolton TAW, Van De Ville D, Régis J, Witjas T, Girard N, Levivier M, Tuleasca C. Graph Theoretical Analysis of Structural Covariance Reveals the Relevance of Visuospatial and Attentional Areas in Essential Tremor Recovery After Stereotactic Radiosurgical Thalamotomy. Front Aging Neurosci 2022; 14:873605. [PMID: 35677202 PMCID: PMC9168220 DOI: 10.3389/fnagi.2022.873605] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Essential tremor (ET) is the most common movement disorder. Its pathophysiology is only partially understood. Here, we leveraged graph theoretical analysis on structural covariance patterns quantified from morphometric estimates for cortical thickness, surface area, and mean curvature in patients with ET before and one year after (to account for delayed clinical effect) ventro-intermediate nucleus (Vim) stereotactic radiosurgical thalamotomy. We further contrasted the observed patterns with those from matched healthy controls (HCs). Significant group differences at the level of individual morphometric properties were specific to mean curvature and the post-/pre-thalamotomy contrast, evidencing brain plasticity at the level of the targeted left thalamus, and of low-level visual, high-level visuospatial and attentional areas implicated in the dorsal visual stream. The introduction of cross-correlational analysis across pairs of morphometric properties strengthened the presence of dorsal visual stream readjustments following thalamotomy, as cortical thickness in the right lingual gyrus, bilateral rostral middle frontal gyrus, and left pre-central gyrus was interrelated with mean curvature in the rest of the brain. Overall, our results position mean curvature as the most relevant morphometric feature to understand brain plasticity in drug-resistant ET patients following Vim thalamotomy. They also highlight the importance of examining not only individual features, but also their interactions, to gain insight into the routes of recovery following intervention.
Collapse
Affiliation(s)
- Thomas A. W. Bolton
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- Connectomics Laboratory, Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Dimitri Van De Ville
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Jean Régis
- Stereotactic and Functional Neurosurgery Service and Gamma Knife Unit, Assistance Publique-Hôpitaux de Marseille, Centre Hospitalier Universitaire de la Timone, Marseille, France
| | - Tatiana Witjas
- Neurology Department, Assistance Publique-Hôpitaux de Marseille, Centre Hospitalier Universitaire de la Timone, Marseille, France
| | - Nadine Girard
- Department of Diagnostic and Interventional Neuroradiology, Centre de Résonance Magnétique Biologique et Médicale, Assistance Publique-Hôpitaux de Marseille, Centre Hospitalier Universitaire de la Timone, Marseille, France
| | - Marc Levivier
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine (FBM), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Constantin Tuleasca
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine (FBM), University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| |
Collapse
|
15
|
Lai H, Kong X, Zhao Y, Pan N, Zhang X, He M, Wang S, Gong Q. Patterns of a structural covariance network associated with dispositional optimism during late adolescence. Neuroimage 2022; 251:119009. [PMID: 35182752 DOI: 10.1016/j.neuroimage.2022.119009] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 01/28/2022] [Accepted: 02/15/2022] [Indexed: 02/08/2023] Open
Abstract
Dispositional optimism (hereinafter, optimism), as a vital character strength, reflects the tendency to hold generalized positive expectancies for future outcomes. A great number of studies have consistently shown the importance of optimism to a spectrum of physical and mental health outcomes. However, less attention has been given to the intrinsic neurodevelopmental patterns associated with interindividual differences in optimism. Here, we investigated this important question in a large sample comprising 231 healthy adolescents (16-20 years old) via structural magnetic resonance imaging and behavioral tests. We constructed individual structural covariance networks based on cortical gyrification using a recent novel approach combining probability density estimation and Kullback-Leibler divergence and estimated global (global efficiency, local efficiency and small-worldness) and regional (betweenness centrality) properties of these constructed networks using graph theoretical analysis. Partial correlations adjusted for age, sex and estimated total intracranial volume showed that optimism was positively related to global and local efficiency but not small-worldness. Partial least squares correlations indicated that optimism was positively linked to a pronounced betweenness centrality pattern, in which twelve cognition-, emotion-, and motivation-related regions made robust and reliable contributions. These findings remained basically consistent after additionally controlling for family socioeconomic status and showed significant correlations with optimism scores from 2.5 years before, which replicated the main findings. The current work, for the first time, delineated characteristics of the cortical gyrification covariance network associated with optimism, extending previous neurobiological understandings of optimism, which may navigate the development of interventions on a neural network level aimed at raising optimism.
Collapse
Affiliation(s)
- Han Lai
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Department of Psychology, Army Medical University, Chongqing, China
| | - Xiangzhen Kong
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - Yajun Zhao
- School of Education and Psychology, Southwest Minzu University, Chengdu, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Xun Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Min He
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
| |
Collapse
|
16
|
Ge X, Zheng Y, Qiao Y, Pan N, Simon JP, Lee M, Jiang W, Kim H, Shi Y, Liu M. Hippocampal Asymmetry of Regional Development and Structural Covariance in Preterm Neonates. Cereb Cortex 2021; 32:4271-4283. [PMID: 34969086 DOI: 10.1093/cercor/bhab481] [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: 06/27/2021] [Revised: 11/21/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022] Open
Abstract
Premature birth is associated with a high prevalence of neurodevelopmental impairments in surviving infants. The hippocampus is known to be critical for learning and memory, yet the putative effects of hippocampal dysfunction remain poorly understood in preterm neonates. In particular, while asymmetry of the hippocampus has been well noted both structurally and functionally, how preterm birth impairs hippocampal development and to what extent the hippocampus is asymmetrically impaired by preterm birth have not been well delineated. In this study, we compared volumetric growth and shape development in the hippocampal hemispheres and structural covariance (SC) between hippocampal vertices and cortical thickness in cerebral cortex regions between two groups. We found that premature infants had smaller volumes of the right hippocampi only. Lower thickness was observed in the hippocampal head in both hemispheres for preterm neonates compared with full-term peers, though preterm neonates exhibited an accelerated age-related change of hippocampal thickness in the left hippocampi. The SC between the left hippocampi and the limbic lobe of the premature infants was severely impaired compared with the term-born neonates. These findings suggested that the development of the hippocampus during the third trimester may be altered following early extrauterine exposure with a high degree of asymmetry.
Collapse
Affiliation(s)
- Xinting Ge
- School of Information Science and Engineering, Shandong Normal University, 250014 Jinan, China.,Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.,School of Medical Imaging, Xuzhou Medical University, 221004 Xuzhou, China
| | - Yuanjie Zheng
- School of Information Science and Engineering, Shandong Normal University, 250014 Jinan, China
| | - Yuchuan Qiao
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ningning Pan
- School of Information Science and Engineering, Shandong Normal University, 250014 Jinan, China
| | - Julia Pia Simon
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Mitchell Lee
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Wenjuan Jiang
- College of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Hosung Kim
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yonggang Shi
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Mengting Liu
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| |
Collapse
|
17
|
King DJ, Seri S, Catroppa C, Anderson VA, Wood AG. Structural-covariance networks identify topology-based cortical-thickness changes in children with persistent executive function impairments after traumatic brain injury. Neuroimage 2021; 244:118612. [PMID: 34563681 PMCID: PMC8591373 DOI: 10.1016/j.neuroimage.2021.118612] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 09/14/2021] [Accepted: 09/20/2021] [Indexed: 11/05/2022] Open
Abstract
Paediatric traumatic brain injury (pTBI) results in inconsistent changes to regional morphometry of the brain across studies. Structural-covariance networks represent the degree to which the morphology (typically cortical-thickness) of cortical-regions co-varies with other regions, driven by both biological and developmental factors. Understanding how heterogeneous regional changes may influence wider cortical network organization may more appropriately capture prognostic information in terms of long term outcome following a pTBI. The current study aimed to investigate the relationships between cortical organisation as measured by structural-covariance, and long-term cognitive impairment following pTBI. T1-weighted magnetic resonance imaging (MRI) from n = 83 pTBI patients and 33 typically developing controls underwent 3D-tissue segmentation using Freesurfer to estimate cortical-thickness across 68 cortical ROIs. Structural-covariance between regions was estimated using Pearson's correlations between cortical-thickness measures across 68 regions-of-interest (ROIs), generating a group-level 68 × 68 adjacency matrix for patients and controls. We grouped a subset of patients who underwent executive function testing at 2-years post-injury using a neuropsychological impairment (NPI) rule, defining impaired- and non-impaired subgroups. Despite finding no significant reductions in regional cortical-thickness between the control and pTBI groups, we found specific reductions in graph-level strength of the structural covariance graph only between controls and the pTBI group with executive function (EF) impairment. Node-level differences in strength for this group were primarily found in frontal regions. We also investigated whether the top n nodes in terms of effect-size of cortical-thickness reductions were nodes that had significantly greater strength in the typically developing brain than n randomly selected regions. We found that acute cortical-thickness reductions post-pTBI are loaded onto regions typically high in structural covariance. This association was found in those patients with persistent EF impairment at 2-years post-injury, but not in those for whom these abilities were spared. This study posits that the topography of post-injury cortical-thickness reductions in regions that are central to the typical structural-covariance topology of the brain, can explain which patients have poor EF at follow-up.
Collapse
Affiliation(s)
- Daniel J King
- College of Health and Life Sciences and Aston Institute of Health and Neurodevelopment, Aston University, Birmingham B4 7ET, UK.
| | - Stefano Seri
- College of Health and Life Sciences and Aston Institute of Health and Neurodevelopment, Aston University, Birmingham B4 7ET, UK; Department of Clinical Neurophysiology, Birmingham Women's and Children's Hospital NHS Foundation Trust, UK
| | - Cathy Catroppa
- Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Department of Psychology, Royal Children's Hospital, Melbourne, Australia
| | - Vicki A Anderson
- Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Department of Psychology, Royal Children's Hospital, Melbourne, Australia
| | - Amanda G Wood
- College of Health and Life Sciences and Aston Institute of Health and Neurodevelopment, Aston University, Birmingham B4 7ET, UK; Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; School of Psychology, Faculty of Health, Melbourne Burwood Campus, Deakin University, Geelong, Victoria, Australia
| |
Collapse
|
18
|
Luo S, Zhu Y, Han S. Functional Connectome Fingerprint of Holistic-Analytic Cultural Style. Soc Cogn Affect Neurosci 2021; 17:172-186. [PMID: 34160613 PMCID: PMC8847908 DOI: 10.1093/scan/nsab080] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 05/25/2021] [Accepted: 06/23/2021] [Indexed: 11/14/2022] Open
Abstract
Although research in the field of cultural psychology and cultural neuroscience has revealed that culture is an important factor related to the human behaviors and neural activities in various tasks, it remains unclear how different brain regions organize together to construct a topological network for the representation of individual's cultural tendency. In this study, we examined the hypothesis that resting-state brain network properties can reflect individual's cultural background or tendency. By combining the methods of resting state MRI and graph theoretical analysis, significant cultural differences between participants from Eastern and Western cultures were found in the degree and global efficiency of regions mainly within the default mode network and subcortical network. Furthermore, the holistic/analytic thinking style, as a cultural value, provided a partial explanation for the cultural differences on various nodal metrics. Validation analyses further confirmed that these network properties effectively predicted the tendency of holistic/analytic cultural style within a group (r = 0.23), and accurately classified cultural groups (65%). The current study establishes a neural connectome representation of holistic/analytic cultural style including the topological brain network properties of regions in the default mode network, the basal ganglia and amygdala, which enable accurate cultural group membership classification.
Collapse
Affiliation(s)
- Siyang Luo
- Department of Psychology, Guangdong Key Laboratory of Social Cognitive Neuroscience and Mental Health, Guangdong Provincial Key Laboratory of Brain Function and Disease, Sun Yat-sen University, Guangzhou 510006, China
| | - Yiyi Zhu
- Department of Psychology, Guangdong Key Laboratory of Social Cognitive Neuroscience and Mental Health, Guangdong Provincial Key Laboratory of Brain Function and Disease, Sun Yat-sen University, Guangzhou 510006, China.,School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Shihui Han
- School of Psychological and Cognitive Sciences, PKU-IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing 100080, China
| |
Collapse
|
19
|
Norbom LB, Ferschmann L, Parker N, Agartz I, Andreassen OA, Paus T, Westlye LT, Tamnes CK. New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings. Prog Neurobiol 2021; 204:102109. [PMID: 34147583 DOI: 10.1016/j.pneurobio.2021.102109] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 06/15/2021] [Indexed: 12/11/2022]
Abstract
Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.
Collapse
Affiliation(s)
- Linn B Norbom
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway
| | - Nadine Parker
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tomáš Paus
- ECOGENE-21, Chicoutimi, Quebec, Canada; Department of Psychology and Psychiatry, University of Toronto, Ontario, Canada; Department of Psychiatry and Centre hospitalier universitaire Sainte-Justine, University of Montreal, Canada
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Christian K Tamnes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| |
Collapse
|
20
|
Simpson-Kent IL, Fried EI, Akarca D, Mareva S, Bullmore ET, Kievit RA. Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners. J Intell 2021; 9:32. [PMID: 34204009 PMCID: PMC8293355 DOI: 10.3390/jintelligence9020032] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/26/2021] [Accepted: 06/02/2021] [Indexed: 12/24/2022] Open
Abstract
Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5-18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role 'between' brain and behavior. We discuss implications and possible avenues for future studies.
Collapse
Affiliation(s)
- Ivan L. Simpson-Kent
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Eiko I. Fried
- Department of Clinical Psychology, Leiden University, 2300 RA Leiden, The Netherlands;
| | - Danyal Akarca
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Silvana Mareva
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Edward T. Bullmore
- Department of Psychiatry, University of Cambridge Clinical School, Cambridge, Cambridgeshire CB2 0SP, UK;
| | - the CALM Team
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Rogier A. Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
- Cognitive Neuroscience Department, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| |
Collapse
|
21
|
Woodburn M, Bricken CL, Wu Z, Li G, Wang L, Lin W, Sheridan MA, Cohen JR. The maturation and cognitive relevance of structural brain network organization from early infancy to childhood. Neuroimage 2021; 238:118232. [PMID: 34091033 PMCID: PMC8372198 DOI: 10.1016/j.neuroimage.2021.118232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 04/30/2021] [Accepted: 06/01/2021] [Indexed: 01/14/2023] Open
Abstract
The interactions of brain regions with other regions at the network level likely provide the infrastructure necessary for cognitive processes to develop. Specifically, it has been theorized that in infancy brain networks become more modular, or segregated, to support early cognitive specialization, before integration across networks increases to support the emergence of higher-order cognition. The present study examined the maturation of structural covariance networks (SCNs) derived from longitudinal cortical thickness data collected between infancy and childhood (0–6 years). We assessed modularity as a measure of network segregation and global efficiency as a measure of network integration. At the group level, we observed trajectories of increasing modularity and decreasing global efficiency between early infancy and six years. We further examined subject-based maturational coupling networks (sbMCNs) in a subset of this cohort with cognitive outcome data at 8–10 years, which allowed us to relate the network organization of longitudinal cortical thickness maturation to cognitive outcomes in middle childhood. We found that lower global efficiency of sbMCNs throughout early development (across the first year) related to greater motor learning at 8–10 years. Together, these results provide novel evidence characterizing the maturation of brain network segregation and integration across the first six years of life, and suggest that specific trajectories of brain network maturation contribute to later cognitive outcomes.
Collapse
Affiliation(s)
- Mackenzie Woodburn
- Department of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States.
| | - Cheyenne L Bricken
- Department of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States
| | - Zhengwang Wu
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States
| | - Gang Li
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States
| | - Li Wang
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States
| | - Weili Lin
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States
| | - Margaret A Sheridan
- Department of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Carolina Institute of Developmental Disabilities, University of North Carolina, Chapel Hill, United States
| | - Jessica R Cohen
- Department of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Carolina Institute of Developmental Disabilities, University of North Carolina, Chapel Hill, United States
| |
Collapse
|
22
|
Xu F, Liu M, Kim SY, Ge X, Zhang Z, Tang Y, Lin X, Toga AW, Liu S, Kim H. Morphological Development Trajectory and Structural Covariance Network of the Human Fetal Cortical Plate during the Early Second Trimester. Cereb Cortex 2021; 31:4794-4807. [PMID: 34017979 DOI: 10.1093/cercor/bhab123] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 04/13/2021] [Accepted: 04/14/2021] [Indexed: 02/07/2023] Open
Abstract
During the early second trimester, the cortical plate, or "the developing cortex", undergoes immensely complex and rapid development to complete its major complement of neurons. However, morphological development of the cortical plate and the precise patterning of brain structural covariance networks during this period remain unexplored. In this study, we used 7.0 T high-resolution magnetic resonance images of brain specimens ranging from 14 to 22 gestational weeks to manually segment the cortical plate. Thickness, area expansion, and curvature (i.e., folding) across the cortical plate regions were computed, and correlations of thickness values among different cortical plate regions were measured to analyze fetal cortico-cortical structural covariance throughout development of the early second trimester. The cortical plate displayed significant increases in thickness and expansions in area throughout all regions but changes of curvature in only certain major sulci. The topological architecture and network properties of fetal brain covariance presented immature and inefficient organizations with low degree of integration and high degree of segregation. Altogether, our results provide novel insight on the developmental patterning of cortical plate thickness and the developmental origin of brain network architecture throughout the early second trimester.
Collapse
Affiliation(s)
- Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan 250012, Shandong, China.,Laboratory of Neuro Imaging (LONI), USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Mengting Liu
- Laboratory of Neuro Imaging (LONI), USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Sharon Y Kim
- Laboratory of Neuro Imaging (LONI), USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Xinting Ge
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.,Laboratory of Neuro Imaging (LONI), USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Zhonghe Zhang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan 250012, Shandong, China
| | - Xiangtao Lin
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan 250012, Shandong, China
| | - Hosung Kim
- Laboratory of Neuro Imaging (LONI), USC Steven Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| |
Collapse
|
23
|
Multivariate Patterns of Brain-Behavior-Environment Associations in the Adolescent Brain and Cognitive Development Study. Biol Psychiatry 2021; 89:510-520. [PMID: 33109338 PMCID: PMC7867576 DOI: 10.1016/j.biopsych.2020.08.014] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 08/17/2020] [Accepted: 08/19/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND Adolescence is a critical developmental stage. A key challenge is to characterize how variation in adolescent brain organization relates to psychosocial and environmental influences. METHODS We used canonical correlation analysis to discover distinct patterns of covariation between measures of brain organization (brain morphometry, intracortical myelination, white matter integrity, and resting-state functional connectivity) and individual, psychosocial, and environmental factors in a nationally representative U.S. sample of 9623 individuals (aged 9-10 years, 49% female) participating in the Adolescent Brain and Cognitive Development (ABCD) study. RESULTS These analyses identified 14 reliable modes of brain-behavior-environment covariation (canonical rdiscovery = .21 to .49, canonical rtest = .10 to .39, pfalse discovery rate corrected < .0001). Across modes, neighborhood environment, parental characteristics, quality of family life, perinatal history, cardiometabolic health, cognition, and psychopathology had the most consistent and replicable associations with multiple measures of brain organization; positive and negative exposures converged to form patterns of psychosocial advantage or adversity. These showed modality-general, respectively positive or negative, associations with brain structure and function with little evidence of regional specificity. Nested within these cross-modal patterns were more specific associations between prefrontal measures of morphometry, intracortical myelination, and functional connectivity with affective psychopathology, cognition, and family environment. CONCLUSIONS We identified clusters of exposures that showed consistent modality-general associations with global measures of brain organization. These findings underscore the importance of understanding the complex and intertwined influences on brain organization and mental function during development and have the potential to inform public health policies aiming toward interventions to improve mental well-being.
Collapse
|
24
|
Richmond S, Beare R, Johnson KA, Allen NB, Seal ML, Whittle S. Towards understanding neurocognitive mechanisms of parenting: Maternal behaviors and structural brain network organization in late childhood. Hum Brain Mapp 2021; 42:1845-1862. [PMID: 33528857 PMCID: PMC7978130 DOI: 10.1002/hbm.25334] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/14/2020] [Accepted: 12/18/2020] [Indexed: 02/07/2023] Open
Abstract
A substantial body of knowledge suggests that exposure to adverse family environments - including violence and neglect - influences many aspects of brain development. Relatively less attention has been directed toward the influence of "normative" differences in parenting behaviors. Given the rapid brain reorganization during late childhood, parenting behaviors are particularly likely to impact the structure of the brain during this time. This study investigated associations between maternal parenting behaviors and the organization of structural brain networks in late childhood, as measured by structural covariance. One hundred and forty-five typically developing 8-year-olds and their mothers completed questionnaire measures and two observed interaction tasks; magnetic resonance imaging (MRI) scans were obtained from the children. Measures of maternal negative, positive, and communicative behavior were derived from the interaction tasks. Structural covariance networks based on partial correlations between cortical thickness estimates were constructed and estimates of modularity were obtained using graph theoretical analysis. High levels of negative maternal behavior were associated with low modularity. Minimal support was found for an association between positive maternal behaviors and modularity and between maternal communicative behaviors and modularity. Our findings suggest that variation in negative maternal behavior is associated with the structural organization of brain networks in children.
Collapse
Affiliation(s)
- Sally Richmond
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia.,Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.,Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Richard Beare
- Department of Developmental Imaging, Murdoch Children's Research Institute, Parkville, Victoria, Australia.,Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - Katherine A Johnson
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Nicholas B Allen
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.,Department of Psychology, University of Oregon, Eugene, Oregon, USA
| | - Marc L Seal
- Department of Developmental Imaging, Murdoch Children's Research Institute, Parkville, Victoria, Australia.,Department for Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia.,Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| |
Collapse
|
25
|
Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study. Mol Psychiatry 2021; 26:4905-4918. [PMID: 32444868 PMCID: PMC7981783 DOI: 10.1038/s41380-020-0757-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 04/21/2020] [Accepted: 04/23/2020] [Indexed: 01/11/2023]
Abstract
Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all PFDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.
Collapse
|
26
|
Beyond the Motor Cortex: Theta Burst Stimulation of the Anterior Midcingulate Cortex. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 5:1052-1060. [PMID: 32839154 DOI: 10.1016/j.bpsc.2020.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND While the facilitatory and inhibitory effects of intermittent theta burst stimulation (iTBS) and continuous TBS (cTBS) protocols have been well documented on motor physiology, the action of TBS protocols on prefrontal functioning remain unclear. Here we asked whether iTBS or cTBS can differentially modulate reward-related signaling in the anterior midcingulate cortex (aMCC). METHODS Across 2 experiments, we used a robot-assisted transcranial magnetic stimulation system, combined with electroencephalogram recordings, to investigate the aftereffects of prefrontal iTBS and cTBS on the reward positivity, an electrophysiological signal believed to index sensitivity of the aMCC to rewards. Twenty adults (age, 18-28 years) participated in experiment 1 in which we used a scalp landmark for TBS targeting, and 14 adults (age, 18-28 years) participated in experiment 2, in which we aimed to increase TBS effectiveness by utilizing cortical thickness maps to select individualized dorsal lateral prefrontal cortex targets. RESULTS We demonstrated that prefrontal iTBS suppressed reward-related signaling in the aMCC (reduction in reward positivity) and caused a decrease in postfeedback switch choices. cTBS displayed no effect. We replicated and strengthened this effect on the reward positivity by targeting dorsal lateral prefrontal cortex regions displaying maximal cortical thickness. CONCLUSIONS While these results are inconsistent with reported TBS effects on motor cortex, the present findings offer a novel transcranial magnetic stimulation targeting approach and normative insights into the magnitude and time course of TBS-induced changes in aMCC excitability. By modulating how the aMCC links value to goal-directed behavior, this research opens an exciting new era of investigative possibilities in the understanding of aMCC function and treatment of aMCC dysfunction.
Collapse
|
27
|
Spanoudis G, Demetriou A. Mapping Mind-Brain Development: Towards a Comprehensive Theory. J Intell 2020; 8:E19. [PMID: 32357452 PMCID: PMC7713015 DOI: 10.3390/jintelligence8020019] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 04/13/2020] [Accepted: 04/20/2020] [Indexed: 12/12/2022] Open
Abstract
The relations between the developing mind and developing brain are explored. We outline a theory of intellectual development postulating that the mind comprises four systems of processes (domain-specific, attention and working memory, reasoning, and cognizance) developing in four cycles (episodic, realistic, rule-based, and principle-based representations, emerging at birth, 2, 6, and 11 years, respectively), with two phases in each. Changes in reasoning relate to processing efficiency in the first phase and working memory in the second phase. Awareness of mental processes is recycled with the changes in each cycle and drives their integration into the representational unit of the next cycle. Brain research shows that each type of processes is served by specialized brain networks. Domain-specific processes are rooted in sensory cortices; working memory processes are mainly rooted in hippocampal, parietal, and prefrontal cortices; abstraction and alignment processes are rooted in parietal, frontal, and prefrontal and medial cortices. Information entering these networks is available to awareness processes. Brain networks change along the four cycles, in precision, connectivity, and brain rhythms. Principles of mind-brain interaction are discussed.
Collapse
Affiliation(s)
- George Spanoudis
- Psychology Department, University of Cyprus, 1678 Nicosia, Cyprus
| | - Andreas Demetriou
- Department of Psychology, University of Nicosia, 1700 Nicosia, Cyprus;
- Cyprus Academy of Science, Letters, and Arts, 1700 Nicosia, Cyprus
| |
Collapse
|
28
|
King DJ, Seri S, Beare R, Catroppa C, Anderson VA, Wood AG. Developmental divergence of structural brain networks as an indicator of future cognitive impairments in childhood brain injury: Executive functions. Dev Cogn Neurosci 2020; 42:100762. [PMID: 32072940 PMCID: PMC6996014 DOI: 10.1016/j.dcn.2020.100762] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 11/01/2019] [Accepted: 01/19/2020] [Indexed: 11/29/2022] Open
Abstract
Brain insults during childhood can perturb the already non-linear trajectory of typical brain maturation. The diffuse effects of injury can be modelled using structural covariance networks (SCN), which change as a function of neurodevelopment. However, SCNs are estimated at the group-level, limiting applicability to predicting individual-subject outcomes. This study aimed to measure the divergence of the brain networks in paediatric traumatic brain injury (pTBI) patients and controls, and investigate relationships with executive functioning (EF) at 24 months post-injury. T1-weighted MRI acquired acutely in 78 child survivors of pTBI and 33 controls underwent 3D-tissue segmentation to estimate cortical thickness (CT) across 68 atlas-based regions-of-interest (ROIs). Using an 'add-one-patient' approach, we estimate a developmental divergence index (DDI). Our approach adopts a novel analytic framework in which age-appropriate reference networks to calculate the DDI were generated from control participants from the ABIDE dataset using a sliding-window approach. Divergence from the age-appropriate SCN was related to reduced EF performance and an increase in behaviours related to executive dysfunctions. The DDI measure showed predictive value with regard to executive functions, highlighting that early imaging can assist in prognosis for cognition.
Collapse
Affiliation(s)
- Daniel J King
- School of Life and Health Sciences & Aston Neuroscience Institute, Aston University, Birmingham, B4 7ET, UK; Department of Clinical Neurophysiology, Birmingham Women's and Children's Hospital NHS Foundation Trust, UK
| | - Stefano Seri
- School of Life and Health Sciences & Aston Neuroscience Institute, Aston University, Birmingham, B4 7ET, UK; Department of Clinical Neurophysiology, Birmingham Women's and Children's Hospital NHS Foundation Trust, UK
| | - Richard Beare
- Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Monash University, Melbourne, Australia
| | - Cathy Catroppa
- Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Department of Psychology, Royal Children's Hospital, Melbourne, Australia
| | - Vicki A Anderson
- Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Department of Psychology, Royal Children's Hospital, Melbourne, Australia
| | - Amanda G Wood
- School of Life and Health Sciences & Aston Neuroscience Institute, Aston University, Birmingham, B4 7ET, UK; Brain and Mind Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; School of Psychology, Faculty of Health, Melbourne Burwood Campus, Deakin University, Geelong, Victoria, Australia.
| |
Collapse
|
29
|
Yun JY, Kim YK. Phenotype Network and Brain Structural Covariance Network of Anxiety. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1191:21-34. [PMID: 32002920 DOI: 10.1007/978-981-32-9705-0_2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Network-based approach for psychological phenotypes assumes the dynamical interactions among the psychiatric symptoms, psychological characteristics, and neurocognitive performances arise, as they coexist, propagate, and inhibit other components within the network of mental phenomena. For differential types of dataset from which the phenotype network is to be estimated, a Gaussian graphical model, an Ising model, a directed acyclic graph, or an intraindividual covariance network could be used. Accordingly, these network-based approaches for anxiety-related psychological phenomena have been helpful in quantitative and pictorial understanding of qualitative dynamics among the diverse psychological phenomena as well as mind-environment interactions. Brain structural covariance refers to the correlative patterns of diverse brain morphological features among differential brain regions comprising the brain, as calculated per participant or across the participants. These covarying patterns of brain morphology partly overlap with longitudinal patterns of brain cortical maturation and also with propagating pattern of brain morphological changes such as cortical thinning and brain volume reduction in patients diagnosed with neurologic or psychiatric disorders along the trajectory of disease progression. Previous studies that used the brain structural covariance network could show neural correlates of specific anxiety disorder such as panic disorder and also elucidate the neural underpinning of anxiety symptom severity in diverse psychiatric and neurologic disorder patients.
Collapse
Affiliation(s)
- Je-Yeon Yun
- Seoul National University Hospital, Seoul, South Korea. .,Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, South Korea.
| | - Yong-Ku Kim
- Department of Psychiatry, College of Medicine, Korea University, Seoul, South Korea
| |
Collapse
|
30
|
Makowski C, Lewis JD, Lepage C, Malla AK, Joober R, Lepage M, Evans AC. Structural Associations of Cortical Contrast and Thickness in First Episode Psychosis. Cereb Cortex 2019; 29:5009-5021. [PMID: 30844050 PMCID: PMC6918925 DOI: 10.1093/cercor/bhz040] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 01/22/2019] [Indexed: 01/22/2023] Open
Abstract
There is growing evidence that psychosis is characterized by brain network abnormalities. Analyzing morphological abnormalities with T1-weighted structural MRI may be limited in discovering the extent of deviations in cortical associations. We assess whether structural associations of either cortical white-gray contrast (WGC) or cortical thickness (CT) allow for a better understanding of brain structural relationships in first episode of psychosis (FEP) patients. Principal component and structural covariance analyses were applied to WGC and CT derived from T1-weighted MRI for 116 patients and 88 controls, to explore sets of brain regions that showed group differences, and associations with symptom severity and cognitive ability in patients. We focused on 2 principal components: one encompassed primary somatomotor regions, which showed trend-like group differences in WGC, and the second included heteromodal cortices. Patients' component scores were related to general psychopathology for WGC, but not CT. Structural covariance analyses with WGC revealed group differences in pairwise correlations across widespread brain regions, mirroring areas derived from PCA. More group differences were uncovered with WGC compared with CT. WGC holds potential as a proxy measure of myelin from commonly acquired T1-weighted MRI and may be sensitive in detecting systems-level aberrations in early psychosis, and relationships with clinical/cognitive profiles.
Collapse
Affiliation(s)
- Carolina Makowski
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
- Department of Psychiatry, McGill University, Verdun, Canada
| | - John D Lewis
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| | - Claude Lepage
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| | - Ashok K Malla
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Ridha Joober
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Martin Lepage
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Alan C Evans
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| |
Collapse
|
31
|
Sawiak SJ, Shiba Y, Oikonomidis L, Windle CP, Santangelo AM, Grydeland H, Cockcroft G, Bullmore ET, Roberts AC. Trajectories and Milestones of Cortical and Subcortical Development of the Marmoset Brain From Infancy to Adulthood. Cereb Cortex 2019; 28:4440-4453. [PMID: 30307494 PMCID: PMC6215464 DOI: 10.1093/cercor/bhy256] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 09/13/2018] [Indexed: 01/04/2023] Open
Abstract
With increasing attention on the developmental causes of neuropsychiatric disorders, appropriate animal models are crucial to identifying causes and assessing potential interventions. The common marmoset is an ideal model as it has sophisticated social/emotional behavior, reaching adulthood within 2 years of birth. Magnetic resonance imaging was used in an accelerated longitudinal cohort (n = 41; aged 3–27 months; scanned 2–7 times over 2 years). Splines were used to model nonlinear trajectories of grey matter volume development in 53 cortical areas and 16 subcortical nuclei. Generally, volumes increased before puberty, peaked, and declined into adulthood. We identified 3 milestones of grey matter development: I) age at peak volume; II) age at onset of volume decline; and III) age at maximum rate of volume decline. These milestones differentiated growth trajectories of primary sensory/motor cortical areas from those of association cortex but also revealed distinct trajectories between association cortices. Cluster analysis of trajectories showed that prefrontal cortex was the most heterogenous of association regions, comprising areas with distinct milestones and developmental trajectories. These results highlight the potential of high-field structural MRI to define the dynamics of primate brain development and importantly to identify when specific prefrontal circuits may be most vulnerable to environmental impact.
Collapse
Affiliation(s)
- S J Sawiak
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Wolfson Brain Imaging Centre, University of Cambridge, Box 65 Addenbrooke's Hospital, Cambridge, UK
| | - Y Shiba
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, UK
| | - L Oikonomidis
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, UK
| | - C P Windle
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, UK
| | - A M Santangelo
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, UK
| | - H Grydeland
- Department of Psychiatry, University of Cambridge, Cambridge, UK.,Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - G Cockcroft
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, UK
| | - E T Bullmore
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Wolfson Brain Imaging Centre, University of Cambridge, Box 65 Addenbrooke's Hospital, Cambridge, UK.,Department of Psychiatry, University of Cambridge, Cambridge, UK.,ImmunoPsychiatry, GlaxoSmithKline Research and Development, Stevenage, UK
| | - A C Roberts
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, UK.,Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, UK
| |
Collapse
|
32
|
Hyatt CS, Owens MM, Crowe ML, Carter NT, Lynam DR, Miller JD. The quandary of covarying: A brief review and empirical examination of covariate use in structural neuroimaging studies on psychological variables. Neuroimage 2019; 205:116225. [PMID: 31568872 DOI: 10.1016/j.neuroimage.2019.116225] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 07/12/2019] [Accepted: 09/23/2019] [Indexed: 12/17/2022] Open
Abstract
Although covarying for potential confounds or nuisance variables is common in psychological research, relatively little is known about how the inclusion of covariates may influence the relations between psychological variables and indices of brain structure. In Part 1 of the current study, we conducted a descriptive review of relevant articles from the past two years of NeuroImage in order to identify the most commonly used covariates in work of this nature. Age, sex, and intracranial volume were found to be the most commonly used covariates, although the number of covariates used ranged from 0 to 14, with 37 different covariate sets across the 68 models tested. In Part 2, we used data from the Human Connectome Project to investigate the degree to which the addition of common covariates altered the relations between individual difference variables (i.e., personality traits, psychopathology, cognitive tasks) and regional gray matter volume (GMV), as well as the statistical significance of values associated with these effect sizes. Using traditional and random sampling approaches, our results varied widely, such that some covariate sets influenced the relations between the individual difference variables and GMV very little, while the addition of other covariate sets resulted in a substantially different pattern of results compared to models with no covariates. In sum, these results suggest that the use of covariates should be critically examined and discussed as part of the conversation on replicability in structural neuroimaging. We conclude by recommending that researchers pre-register their analytic strategy and present information on how relations differ based on the inclusion of covariates.
Collapse
Affiliation(s)
| | - Max M Owens
- University of Georgia, USA; University of Vermont, USA
| | | | | | | | | |
Collapse
|
33
|
Esteban-Cornejo I, Mora-Gonzalez J, Cadenas-Sanchez C, Contreras-Rodriguez O, Verdejo-Román J, Henriksson P, Migueles JH, Rodriguez-Ayllon M, Molina-García P, Suo C, Hillman CH, Kramer AF, Erickson KI, Catena A, Verdejo-García A, Ortega FB. Fitness, cortical thickness and surface area in overweight/obese children: The mediating role of body composition and relationship with intelligence. Neuroimage 2019; 186:771-781. [DOI: 10.1016/j.neuroimage.2018.11.047] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 11/05/2018] [Accepted: 11/26/2018] [Indexed: 12/27/2022] Open
|
34
|
Qian X, Castellanos FX, Uddin LQ, Loo BRY, Liu S, Koh HL, Poh XWW, Fung D, Guan C, Lee TS, Lim CG, Zhou J. Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder. Neuroimage Clin 2018; 21:101600. [PMID: 30472167 PMCID: PMC6411599 DOI: 10.1016/j.nicl.2018.11.010] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 11/13/2018] [Accepted: 11/16/2018] [Indexed: 02/04/2023]
Abstract
Accumulating evidence suggests brain network dysfunction in attention-deficit/hyperactivity disorder (ADHD). Whether large-scale brain network connectivity patterns reflect clinical heterogeneity in ADHD remains to be fully understood. This study aimed to characterize the differential within- and between-network functional connectivity (FC) changes in children with ADHD combined (ADHD-C) or inattentive (ADHD-I) subtypes and their associations with ADHD symptoms. We studied the task-free functional magnetic resonance imaging (fMRI) data of 58 boys with ADHD and 28 demographically matched healthy controls. We measured within- and between-network connectivity of both low-level (sensorimotor) and high-level (cognitive) large-scale intrinsic connectivity networks and network modularity. We found that children with ADHD-C but not those with ADHD-I exhibited hyper-connectivity within the anterior default mode network (DMN) compared with controls. Additionally, children with ADHD-C had higher inter-network FC between the left executive control (ECN) and the salience (SN) networks, between subcortical and visual networks, and between the DMN and left auditory networks than controls, while children with ADHD-I did not show differences compared with controls. Similarly, children with ADHD-C but not ADHD-I showed lower network modularity compared with controls. Importantly, these observed abnormal inter-network connectivity and network modularity metrics were associated with Child Behavioral Checklist (CBCL) attention-deficit/hyperactivity problems and internalizing problems in children with ADHD. This study revealed relatively greater loss of brain functional network segregation in childhood ADHD combined subtype compared to the inattentive subtype, suggesting differential large-scale functional brain network topology phenotype underlying childhood ADHD heterogeneity.
Collapse
Affiliation(s)
- Xing Qian
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, 8 College Road, Singapore 169857, Singapore
| | | | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, United States
| | - Beatrice Rui Yi Loo
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, 8 College Road, Singapore 169857, Singapore
| | - Siwei Liu
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, 8 College Road, Singapore 169857, Singapore
| | - Hui Li Koh
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, 8 College Road, Singapore 169857, Singapore
| | - Xue Wei Wendy Poh
- Department of Child and Adolescent Psychiatry, Institute of Mental Health, Singapore, Singapore
| | - Daniel Fung
- Department of Child and Adolescent Psychiatry, Institute of Mental Health, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Tih-Shih Lee
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, 8 College Road, Singapore 169857, Singapore
| | - Choon Guan Lim
- Department of Child and Adolescent Psychiatry, Institute of Mental Health, Singapore, Singapore
| | - Juan Zhou
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, 8 College Road, Singapore 169857, Singapore; Clinical Imaging Research Centre, The Agency for Science, Technology and Research-National University of Singapore, Singapore, Singapore.
| |
Collapse
|
35
|
Tian F, Chen Q, Zhu W, Wang Y, Yang W, Zhu X, Tian X, Zhang Q, Cao G, Qiu J. The association between visual creativity and cortical thickness in healthy adults. Neurosci Lett 2018; 683:104-110. [PMID: 29936269 DOI: 10.1016/j.neulet.2018.06.036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Revised: 06/12/2018] [Accepted: 06/20/2018] [Indexed: 01/30/2023]
Abstract
Creativity is necessary to human survival, human prosperity, civilization and well-being. Visual creativity is an important part of creativity and is the ability to create products of novel and useful visual forms, playing important role in many fields such as art, painting and sculpture. There have been several neuroimaging studies exploring the neural basis of visual creativity. However, to date, little is known about the relationship between cortical structure and visual creativity as measured by the Torrance Tests of Creative Thinking. Here, we investigated the association between cortical thickness and visual creativity in a large sample of 310 healthy adults. We used multiple regression to analyze the correlation between cortical thickness and visual creativity, adjusting for gender, age and general intelligence. The results showed that visual creativity was significantly negatively correlated with cortical thickness in the left middle frontal gyrus (MFG), right inferior frontal gyrus (IFG), right supplementary motor cortex (SMA) and the left insula. These observations have implications for understanding that a thinner prefrontal cortex (PFC) (e.g. IFG, MFG), SMA and insula correspond to higher visual creative performance, presumably due to their role in executive attention, cognitive control, motor planning and dynamic switching.
Collapse
Affiliation(s)
- Fang Tian
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Qunlin Chen
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Wenfeng Zhu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Yongming Wang
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Wenjing Yang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Xingxing Zhu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Xue Tian
- Faculty of Psychology, Beijing Normal University, Beijing, 100190, China
| | - Qinglin Zhang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Guikang Cao
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China.
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China.
| |
Collapse
|
36
|
Sandini C, Zöller D, Scariati E, Padula MC, Schneider M, Schaer M, Van De Ville D, Eliez S. Development of Structural Covariance From Childhood to Adolescence: A Longitudinal Study in 22q11.2DS. Front Neurosci 2018; 12:327. [PMID: 29867336 PMCID: PMC5968113 DOI: 10.3389/fnins.2018.00327] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 04/26/2018] [Indexed: 12/18/2022] Open
Abstract
Background: Schizophrenia is currently considered a neurodevelopmental disorder of connectivity. Still few studies have investigated how brain networks develop in children and adolescents who are at risk for developing psychosis. 22q11.2 Deletion Syndrome (22q11DS) offers a unique opportunity to investigate the pathogenesis of schizophrenia from a neurodevelopmental perspective. Structural covariance (SC) is a powerful approach to explore morphometric relations between brain regions that can furthermore detect biomarkers of psychosis, both in 22q11DS and in the general population. Methods: Here we implement a state-of-the-art sliding-window approach to characterize maturation of SC network architecture in a large longitudinal cohort of patients with 22q11DS (110 with 221 visits) and healthy controls (117 with 211 visits). We furthermore propose a new clustering-based approach to group regions according to trajectories of structural connectivity maturation. We correlate measures of SC with development of working memory, a core executive function that is highly affected in both idiopathic psychosis and 22q11DS. Finally, in 22q11DS we explore correlations between SC dysconnectivity and severity of internalizing psychopathology. Results: In HCs network architecture underwent a quadratic developmental trajectory maturing up to mid-adolescence. Late-childhood maturation was particularly evident for fronto-parietal cortices, while Default-Mode-Network-related regions showed a more protracted linear development. Working memory performance was positively correlated with network segregation and fronto-parietal connectivity. In 22q11DS, we demonstrate aberrant maturation of SC with disturbed architecture selectively emerging during adolescence and correlating more severe internalizing psychopathology. Patients also presented a lack of typical network development during late-childhood, that was particularly prominent for frontal connectivity. Conclusions: Our results suggest that SC maturation may underlie critical cognitive development occurring during late-childhood in healthy controls. Aberrant trajectories of SC maturation may reflect core developmental features of 22q11DS, including disturbed cognitive maturation during childhood and predisposition to internalizing psychopathology and psychosis during adolescence.
Collapse
Affiliation(s)
- Corrado Sandini
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland
| | - Daniela Zöller
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland.,Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Elisa Scariati
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland
| | - Maria C Padula
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland
| | - Maude Schneider
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland.,Department of Neuroscience, Center for Contextual Psychiatry, Research Group Psychiatry, KU Leuven, Leuven, Belgium
| | - Marie Schaer
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland
| | - Dimitri Van De Ville
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Stephan Eliez
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland.,Department of Genetic Medicine and Development, University of Geneva School of Medicine, Geneva, Switzerland
| |
Collapse
|
37
|
Gilmore JH, Knickmeyer RC, Gao W. Imaging structural and functional brain development in early childhood. Nat Rev Neurosci 2018; 19:123-137. [PMID: 29449712 PMCID: PMC5987539 DOI: 10.1038/nrn.2018.1] [Citation(s) in RCA: 454] [Impact Index Per Article: 75.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In humans, the period from term birth to ∼2 years of age is characterized by rapid and dynamic brain development and plays an important role in cognitive development and risk of disorders such as autism and schizophrenia. Recent imaging studies have begun to delineate the growth trajectories of brain structure and function in the first years after birth and their relationship to cognition and risk of neuropsychiatric disorders. This Review discusses the development of grey and white matter and structural and functional networks, as well as genetic and environmental influences on early-childhood brain development. We also discuss initial evidence regarding the usefulness of early imaging biomarkers for predicting cognitive outcomes and risk of neuropsychiatric disorders.
Collapse
Affiliation(s)
- John H Gilmore
- Department of Psychiatry, CB# 7160, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Rebecca C Knickmeyer
- Department of Psychiatry, CB# 7160, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, University of California, Los Angeles, CA, USA
| |
Collapse
|
38
|
Abstract
A complex system can be represented and analyzed as a network, where nodes represent the units of the network and edges represent connections between those units. For example, a brain network represents neurons as nodes and axons between neurons as edges. In many networks, some nodes have a disproportionately high number of edges as well as many edges between each other and are referred to as the "rich club". In many different networks, the nodes of this club are assumed to support global network integration. Here we show that another set of nodes, which have edges diversely distributed across the network, form a "diverse club". The diverse club exhibits, to a greater extent than the rich club, properties consistent with an integrative network function-these nodes are more highly interconnected and their edges are more critical for efficient global integration. Finally, these two clubs potentially evolved via distinct selection pressures.
Collapse
Affiliation(s)
- M A Bertolero
- Helen Wills Neuroscience Institute and Department of Psychology, University of California Berkeley, 132 Barker Hall Berkeley, Berkeley, CA, 94720, USA.
- Department of Bioengineering, University of Pennsylvania, Hayden Hall 318C, Philadelphia, PA, 19104, USA.
| | - B T T Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 119077, Singapore
- Clinical Imaging Research Centre, National University of Singapore, Singapore, 117599, Singapore
- Singapore Institute for Neurotechnology, National University of Singapore, Singapore, 117456, Singapore
- Memory Networks Programme, National University of Singapore, Singapore, 119077, Singapore
| | - M D'Esposito
- Helen Wills Neuroscience Institute and Department of Psychology, University of California Berkeley, 132 Barker Hall Berkeley, Berkeley, CA, 94720, USA
| |
Collapse
|
39
|
Brain Structural Networks Associated with Intelligence and Visuomotor Ability. Sci Rep 2017; 7:2177. [PMID: 28526888 PMCID: PMC5438383 DOI: 10.1038/s41598-017-02304-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Accepted: 04/07/2017] [Indexed: 02/05/2023] Open
Abstract
Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions.
Collapse
|
40
|
Rinaldi L, Karmiloff-Smith A. Intelligence as a Developing Function: A Neuroconstructivist Approach. J Intell 2017; 5:E18. [PMID: 31162409 PMCID: PMC6526422 DOI: 10.3390/jintelligence5020018] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Revised: 04/21/2017] [Accepted: 04/27/2017] [Indexed: 11/16/2022] Open
Abstract
The concept of intelligence encompasses the mental abilities necessary to survival and advancement in any environmental context. Attempts to grasp this multifaceted concept through a relatively simple operationalization have fostered the notion that individual differences in intelligence can often be expressed by a single score. This predominant position has contributed to expect intelligence profiles to remain substantially stable over the course of ontogenetic development and, more generally, across the life-span. These tendencies, however, are biased by the still limited number of empirical reports taking a developmental perspective on intelligence. Viewing intelligence as a dynamic concept, indeed, implies the need to identify full developmental trajectories, to assess how genes, brain, cognition, and environment interact with each other. In the present paper, we describe how a neuroconstructivist approach better explains why intelligence can rise or fall over development, as a result of a fluctuating interaction between the developing system itself and the environmental factors involved at different times across ontogenesis.
Collapse
Affiliation(s)
- Luca Rinaldi
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia 27100, Italy.
- Milan Center for Neuroscience, Milano 20126, Italy.
| | | |
Collapse
|