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Lewis JD, Imani V, Tohka J. Intelligence and cortical morphometry: caveats in brain-behavior associations. Brain Struct Funct 2024; 229:1417-1432. [PMID: 38795129 PMCID: PMC11176253 DOI: 10.1007/s00429-024-02792-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 03/19/2024] [Indexed: 05/27/2024]
Abstract
It is well-established that brain size is associated with intelligence. But the relationship between cortical morphometric measures and intelligence is unclear. Studies have produced conflicting results or no significant relations between intelligence and cortical morphometric measures such as cortical thickness and peri-cortical contrast. This discrepancy may be due to multicollinearity amongst the independent variables in a multivariate regression analysis, or a failure to fully account for the relationship between brain size and intelligence in some other way. Our study shows that neither cortical thickness nor peri-cortical contrast reliably improves IQ prediction accuracy beyond what is achieved with brain volume alone. We show this in multiple datasets, with child data, developmental data, and with adult data; we show this with data acquired either at multiple sites, or at a single site; we show this with data acquired with different MRI scanner manufacturers, or with all data acquired on a single scanner; and we show this with fluid intelligence, full-scale IQ, performance IQ, and verbal IQ. But our point is not really even about IQ; rather we proffer a methodological caveat and potential explanation of the discrepancies in previous results, and which applies broadly.
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Affiliation(s)
- John D Lewis
- Program in Neuroscience and Mental Health, The Hospital for Sick Children Research Institute, 555 University Avenue, Toronto, ON, M5G1X8, Canada
| | - Vandad Imani
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70210, Kuopio, Finland
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70210, Kuopio, Finland.
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Yang J, Chen C, Chen N, Zheng H, Chen Y, Li X, Jia Q, Li T. Clinical characteristics and rehabilitation potential in children with cerebral palsy based on MRI classification system. Front Pediatr 2024; 12:1382172. [PMID: 38725982 PMCID: PMC11079180 DOI: 10.3389/fped.2024.1382172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/09/2024] [Indexed: 05/12/2024] Open
Abstract
Background The correlation of clinical characteristics of cerebral palsy (CP) and the magnetic resonance imaging classification system (MRICS) for (CP) is inconsistent. Specifically, the variance in rehabilitation potential across MRICS remains underexplored. Aims To investigate the clinical characteristics and potential for rehabilitation in children with CP based on MRICS. Materials and methods Children with CP admitted to the Department of Rehabilitation, Children's Hospital of Chongqing Medical University between 2017 and 2021 were included in the study. Qualified cases underwent a follow-up period of at least one year. The clinical characteristics of CP among different MRICS were analyzed, then the rehabilitation potential was explored by a retrospective cohort study. Results Among the 384 initially enrolled children, the male-to-female ratio was 2.3:1, and the median age of diagnosis was 6.5 months (interquartile range: 4-12). The most prevalent MRICS categorization was predominant white matter injury (40.6%), followed by miscellaneous (29.2%) and predominant gray matter injury (15.6%). For the predominant white matter injury and miscellaneous categories, spastic diplegia emerged as the leading subtype of CP, with incidences of 59.6% and 36.6%, respectively, while mixed CP (36.7%) was the most common type in children with predominant gray matter. Notably, 76.4% of children with predominant white matter injury were classified as levels I-III on the gross motor function classification system (GMFCS), indicating significantly less severity than other groups (χ2 = 12.438, p = 0.013). No significant difference across MRICS categories was observed for the manual ability classification system (MACS) (H = 8.176, p = 0.085). Rehabilitation potential regarding fine motor function and adaptability based on Gesell assessment was dependent on MRICS over the follow-up period. Children with normal MRI scans exhibited superior rehabilitation outcomes. Commencing rehabilitation at an earlier stage produced consistent and beneficial results in terms of fine motor function and adaptability across all MRICS categories. Moreover, participants below 2 years of age demonstrated enhanced rehabilitation potential regarding fine motor outcomes and adaptability within the MRICS framework. Conclusion MRICS displayed a significant association with clinical characteristics and rehabilitation efficacy in children with CP.
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Affiliation(s)
- Jie Yang
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Congjie Chen
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Ningning Chen
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Helin Zheng
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
- Department of Radiology, CHCMU, Chongqing, China
| | - Yuxia Chen
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Xiaoli Li
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Qingxia Jia
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Tingsong Li
- Department of Rehabilitation, Children’s Hospital of Chongqing Medical University (CHCMU), Chongqing, China
- National Clinical Research Center for Child Health and Disorders, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Chongqing, China
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Sun YJ, Sahakian BJ, Langley C, Yang A, Jiang Y, Kang J, Zhao X, Li C, Cheng W, Feng J. Early-initiated childhood reading for pleasure: associations with better cognitive performance, mental well-being and brain structure in young adolescence. Psychol Med 2024; 54:359-373. [PMID: 37376848 DOI: 10.1017/s0033291723001381] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
BACKGROUND Childhood is a crucial neurodevelopmental period. We investigated whether childhood reading for pleasure (RfP) was related to young adolescent assessments of cognition, mental health, and brain structure. METHODS We conducted a cross-sectional and longitudinal study in a large-scale US national cohort (10 000 + young adolescents), using the well-established linear mixed model and structural equation methods for twin study, longitudinal and mediation analyses. A 2-sample Mendelian randomization (MR) analysis for potential causal inference was also performed. Important factors including socio-economic status were controlled. RESULTS Early-initiated long-standing childhood RfP (early RfP) was highly positively correlated with performance on cognitive tests and significantly negatively correlated with mental health problem scores of young adolescents. These participants with higher early RfP scores exhibited moderately larger total brain cortical areas and volumes, with increased regions including the temporal, frontal, insula, supramarginal; left angular, para-hippocampal; right middle-occipital, anterior-cingulate, orbital areas; and subcortical ventral-diencephalon and thalamus. These brain structures were significantly related to their cognitive and mental health scores, and displayed significant mediation effects. Early RfP was longitudinally associated with higher crystallized cognition and lower attention symptoms at follow-up. Approximately 12 h/week of youth regular RfP was cognitively optimal. We further observed a moderately significant heritability of early RfP, with considerable contribution from environments. MR analysis revealed beneficial causal associations of early RfP with adult cognitive performance and left superior temporal structure. CONCLUSIONS These findings, for the first time, revealed the important relationships of early RfP with subsequent brain and cognitive development and mental well-being.
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Affiliation(s)
- Yun-Jun Sun
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Barbara J Sahakian
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Christelle Langley
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Anyi Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Yuchao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Xingming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Chunhe Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Zhangjiang Fudan International Innovation Center, Shanghai, China
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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.
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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.
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de Souza EA, Silva SA, Vieira BH, Salmon CEG. fMRI functional connectivity is a better predictor of general intelligence than cortical morphometric features and ICA parcellation order affects predictive performance. INTELLIGENCE 2023. [DOI: 10.1016/j.intell.2023.101727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Andreou D, Jørgensen KN, Nerland S, Ueland T, Vaskinn A, Haukvik UK, Yolken RH, Andreassen OA, Agartz I. Herpes simplex virus 1 infection on grey matter and general intelligence in severe mental illness. Transl Psychiatry 2022; 12:276. [PMID: 35821107 PMCID: PMC9276804 DOI: 10.1038/s41398-022-02044-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 06/22/2022] [Accepted: 06/29/2022] [Indexed: 11/09/2022] Open
Abstract
Schizophrenia and bipolar disorder are severe mental illnesses (SMI) linked to both genetic and environmental factors. Herpes simplex virus 1 (HSV1) is a common neurotropic pathogen which after the primary infection establishes latency with periodic reactivations. We hypothesized that the latent HSV1 infection is associated with brain structural abnormalities and cognitive impairment, especially in SMI. We included 420 adult patients with SMI (schizophrenia or bipolar spectrum) and 481 healthy controls. Circulating HSV1 immunoglobulin G concentrations were measured with immunoassays. We measured the total grey matter volume (TGMV), cortical, subcortical, cerebellar and regional cortical volumes based on T1-weighted MRI scans processed in FreeSurfer v6.0.0. Intelligence quotient (IQ) was assessed with the Wechsler Abbreviated Scale of Intelligence. Seropositive patients had significantly smaller TGMV than seronegative patients (642 cm3 and 654 cm3, respectively; p = 0.019) and lower IQ (104 and 107, respectively; p = 0.018). No TGMV or IQ differences were found between seropositive and seronegative healthy controls. Post-hoc analysis showed that (a) in both schizophrenia and bipolar spectrum, seropositive patients had similarly smaller TGMV than seronegative patients, whereas the HSV1-IQ association was driven by the schizophrenia spectrum group, and (b) among all patients, seropositivity was associated with smaller total cortical (p = 0.016), but not subcortical or cerebellar grey matter volumes, and with smaller left caudal middle frontal, precentral, lingual, middle temporal and banks of superior temporal sulcus regional cortical grey matter volumes. The results of this cross-sectional study indicate that HSV1 may be an environmental factor associated with brain structural abnormalities and cognitive impairment in SMI.
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Affiliation(s)
- Dimitrios Andreou
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway. .,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway. .,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden.
| | - Kjetil Nordbø Jørgensen
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.413684.c0000 0004 0512 8628Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Stener Nerland
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.413684.c0000 0004 0512 8628Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Torill Ueland
- grid.55325.340000 0004 0389 8485Psychosis Research Section, Oslo University Hospital, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Anja Vaskinn
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Centre for Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Unn K. Haukvik
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway ,grid.55325.340000 0004 0389 8485Centre for Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Robert H. Yolken
- grid.21107.350000 0001 2171 9311Stanley Division of Developmental Neurovirology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Ole A. Andreassen
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.413684.c0000 0004 0512 8628Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway ,grid.425979.40000 0001 2326 2191Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
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Vieira BH, Pamplona GSP, Fachinello K, Silva AK, Foss MP, Salmon CEG. On the prediction of human intelligence from neuroimaging: A systematic review of methods and reporting. INTELLIGENCE 2022. [DOI: 10.1016/j.intell.2022.101654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Ash H, Chang A, Ortiz RJ, Kulkarni P, Rauch B, Colman R, Ferris CF, Ziegler TE. Structural and functional variations in the prefrontal cortex are associated with learning in pre-adolescent common marmosets (Callithrix jacchus). Behav Brain Res 2022; 430:113920. [PMID: 35595058 PMCID: PMC9362994 DOI: 10.1016/j.bbr.2022.113920] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 04/06/2022] [Accepted: 05/04/2022] [Indexed: 12/27/2022]
Abstract
There is substantial evidence linking the prefrontal cortex (PFC) to a variety of cognitive abilities, with adolescence being a critical period in its development. In the current study, we investigated the neural basis of differences in learning in pre-adolescent common marmosets. At 8 months old, marmosets were given anatomical and resting state MRI scans (n=24). At 9 months old, association learning and inhibitory control was tested using a 'go/no go' visual discrimination (VD) task. Marmosets were grouped into 'learners' (n=12) and 'non-learners' (n=12), and associations between cognitive performance and sub-regional PFC volumes, as well as PFC connectivity patterns, were investigated. 'Learners' had significantly (p<0.05) larger volumes of areas 11, 25, 47 and 32 than 'non-learners', although 'non-learners' had significantly larger volumes of areas 24a and 8v than 'learners'. There was also a significant correlation between average % correct responses to the 'punished' stimulus and volume of area 47. Further, 'non-learners' had significantly greater global PFC connections, as well as significantly greater numbers of connections between the PFC and basal ganglia, cerebellum and hippocampus, compared to 'non-learners'. These results suggest that larger sub-regions of the orbitofrontal cortex and ventromedial PFC, as well more refined PFC connectivity patterns to other brain regions associated with learning, may be important in successful response inhibition. This study therefore offers new information on the neurodevelopment of individual differences in cognition during pre-adolescence in non-human primates.
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Affiliation(s)
- Hayley Ash
- Wisconsin National Primate Research Center, University of Wisconsin, Madison WI.
| | - Arnold Chang
- Center for Translational NeuroImaging, Northeastern University, Boston MA
| | - Richard J Ortiz
- Center for Translational NeuroImaging, Northeastern University, Boston MA; Department of Chemistry and Biochemistry, New Mexico State University, Las Cruces NM
| | - Praveen Kulkarni
- Center for Translational NeuroImaging, Northeastern University, Boston MA
| | - Beth Rauch
- Department of Medical Physics, University of Wisconsin, Madison WI
| | - Ricki Colman
- Wisconsin National Primate Research Center, University of Wisconsin, Madison WI; Department of Cell and Regenerative Biology, University of Wisconsin, Madison WI
| | - Craig F Ferris
- Center for Translational NeuroImaging, Northeastern University, Boston MA
| | - Toni E Ziegler
- Wisconsin National Primate Research Center, University of Wisconsin, Madison WI
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Raja R, Na X, Moore A, Otoo R, Glasier CM, Badger TM, Ou X. Associations Between White Matter Microstructures and Cognitive Functioning in 8-Year-Old Children: A Track-Weighted Imaging Study. J Child Neurol 2022; 37:471-490. [PMID: 35254148 PMCID: PMC9149064 DOI: 10.1177/08830738221083487] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE Quantitative tractography using diffusion-weighted magnetic resonance imaging data is widely used in characterizing white matter microstructure throughout childhood, but more studies are still needed to investigate comprehensive brain-behavior relationships between tract-specific white matter measures and multiple cognitive functions in children. METHODS In this study, we analyzed diffusion-weighted MRI data of 71 healthy 8-year-old children utilizing white matter tract-specific quantitative measures derived from diffusion-weighted MRI tractography based on a novel track-weighted imaging approach. Track density imaging, average path length map and 4 track-weighted diffusion tensor imaging measures including: mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for 63 white matter tracts. The track-weighted imaging measures were then correlated with a comprehensive set of neuropsychological test scores in different cognitive domains including intelligence, language, memory, academic skills, and executive functions to identify tract-specific brain-behavior relationships. RESULTS Significant correlations (P < .05, false discovery rate corrected; r = 0.27-0.57) were found in multiple white matter tracts, with a total of 40 correlations identified between various track-weighted imaging measures including average path length map, track-weighted imaging-fractional anisotropy, and neuropsychological test scores and subscales. Specifically, track-weighted imaging measures indicative of better white matter connectivity and/or microstructural development significantly correlated with higher IQ and better language abilities. CONCLUSION Our findings demonstrate the ability of track-weighted imaging measures in establishing associations between white matter and cognitive functioning in healthy children and can serve as a reference for normal brain/cognition relationships in young school-age children and further aid in identifying imaging biomarkers predictive of adverse neurodevelopmental outcomes.
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Affiliation(s)
- Rajikha Raja
- Department of Radiology, University of Arkansas for Medical Sciences
| | - Xiaoxu Na
- Department of Radiology, University of Arkansas for Medical Sciences
| | - Alexandra Moore
- College of Medicine, University of Arkansas for Medical Sciences
| | - Raymond Otoo
- College of Medicine, University of Arkansas for Medical Sciences
| | - Charles M. Glasier
- Department of Radiology, University of Arkansas for Medical Sciences,Department of Pediatrics, University of Arkansas for Medical Sciences
| | - Thomas M. Badger
- Department of Pediatrics, University of Arkansas for Medical Sciences,Arkansas Children’s Nutrition Center
| | - Xiawei Ou
- Department of Radiology, University of Arkansas for Medical Sciences,Department of Pediatrics, University of Arkansas for Medical Sciences
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Drakulich S, Sitartchouk A, Olafson E, Sarhani R, Thiffault AC, Chakravarty M, Evans AC, Karama S. General cognitive ability and pericortical contrast. INTELLIGENCE 2022. [DOI: 10.1016/j.intell.2022.101633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Kovac V, Shapiro EG, Rudser KD, Mueller BA, Eisengart JB, Delaney KA, Ahmed A, King KE, Yund BD, Cowan MJ, Raiman J, Mamak EG, Harmatz PR, Shankar SP, Ali N, Cagle SR, Wozniak JR, Lim KO, Orchard PJ, Whitley CB, Nestrasil I. Quantitative brain MRI morphology in severe and attenuated forms of mucopolysaccharidosis type I. Mol Genet Metab 2022; 135:122-132. [PMID: 35012890 PMCID: PMC8898074 DOI: 10.1016/j.ymgme.2022.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 01/04/2022] [Accepted: 01/04/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess our hypothesis that brain macrostructure is different in individuals with mucopolysaccharidosis type I (MPS I) and healthy controls (HC), we conducted a comprehensive multicenter study using a uniform quantitative magnetic resonance imaging (qMRI) protocol, with analyses that account for the effects of disease phenotype, age, and cognition. METHODS Brain MRIs in 23 individuals with attenuated (MPS IA) and 38 with severe MPS I (MPS IH), aged 4-25 years, enrolled under the study protocol NCT01870375, were compared to 98 healthy controls. RESULTS Cortical and subcortical gray matter, white matter, corpus callosum, ventricular and choroid plexus volumes in MPS I significantly differed from HC. Thicker cortex, lower white matter and corpus callosum volumes were already present at the youngest MPS I participants aged 4-5 years. Age-related differences were observed in both MPS I groups, but most markedly in MPS IH, particularly in cortical gray matter metrics. IQ scores were inversely associated with ventricular volume in both MPS I groups and were positively associated with cortical thickness only in MPS IA. CONCLUSIONS Quantitatively-derived MRI measures distinguished MPS I participants from HC as well as severe from attenuated forms. Age-related neurodevelopmental trajectories in both MPS I forms differed from HC. The extent to which brain structure is altered by disease, potentially spared by treatment, and how it relates to neurocognitive dysfunction needs further exploration.
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Affiliation(s)
- Victor Kovac
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Elsa G Shapiro
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Kyle D Rudser
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
| | - Bryon A Mueller
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
| | - Julie B Eisengart
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Kathleen A Delaney
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Alia Ahmed
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Kelly E King
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Brianna D Yund
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Morton J Cowan
- UCSF Benioff Children's Hospital, University of California, San Francisco, CA, USA.
| | - Julian Raiman
- Division of Clinical and Metabolic Genetics, Department of Paediatrics, University of Toronto, The Hospital for Sick Children, Toronto, ON, Canada.
| | - Eva G Mamak
- Department of Psychology, The Hospital for Sick Children, Toronto, ON, Canada.
| | - Paul R Harmatz
- UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA.
| | - Suma P Shankar
- Department of Ophthalmology and Human Genetics, Emory University, Atlanta, GA, USA.
| | - Nadia Ali
- Department of Human Genetics, Emory University, Atlanta, GA, USA.
| | | | - Jeffrey R Wozniak
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
| | - Kelvin O Lim
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
| | - Paul J Orchard
- Division of Pediatric Blood & Marrow Transplantation, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Chester B Whitley
- Gene Therapy Center, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Igor Nestrasil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Center for Magnetic Resonance Research (CMRR), Department of Radiology, Minneapolis, MN, USA.
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13
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Hebling Vieira B, Dubois J, Calhoun VD, Garrido Salmon CE. A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRI. Hum Brain Mapp 2021; 42:5873-5887. [PMID: 34587333 PMCID: PMC8596958 DOI: 10.1002/hbm.25656] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 11/30/2022] Open
Abstract
Prediction of cognitive ability latent factors such as general intelligence from neuroimaging has elucidated questions pertaining to their neural origins. However, predicting general intelligence from functional connectivity limit hypotheses to that specific domain, being agnostic to time‐distributed features and dynamics. We used an ensemble of recurrent neural networks to circumvent this limitation, bypassing feature extraction, to predict general intelligence from resting‐state functional magnetic resonance imaging regional signals of a large sample (n = 873) of Human Connectome Project adult subjects. Ablating common resting‐state networks (RSNs) and measuring degradation in performance, we show that model reliance can be mostly explained by network size. Using our approach based on the temporal variance of saliencies, that is, gradients of outputs with regards to inputs, we identify a candidate set of networks that more reliably affect performance in the prediction of general intelligence than similarly sized RSNs. Our approach allows us to further test the effect of local alterations on data and the expected changes in derived metrics such as functional connectivity and instantaneous innovations.
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Affiliation(s)
- Bruno Hebling Vieira
- InBrain Lab, Departamento de Física, Universidade de São Paulo, Ribeirão Preto, Brazil.,Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Julien Dubois
- Cedars-Sinai Medical Center, Los Angeles, California, USA.,Caltech, Pasadena, California, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA.,The Mind Research Network, Albuquerque, New Mexico, USA.,School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
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14
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Marshall AT, McConnell R, Lanphear BP, Thompson WK, Herting MM, Sowell ER. Risk of lead exposure, subcortical brain structure, and cognition in a large cohort of 9- to 10-year-old children. PLoS One 2021; 16:e0258469. [PMID: 34648580 PMCID: PMC8516269 DOI: 10.1371/journal.pone.0258469] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 09/26/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Lead, a toxic metal, affects cognitive development at the lowest measurable concentrations found in children, but little is known about its direct impact on brain development. Recently, we reported widespread decreases in cortical surface area and volume with increased risks of lead exposure, primarily in children of low-income families. METHODS AND FINDINGS We examined associations of neighborhood-level risk of lead exposure with cognitive test performance and subcortical brain volumes. We also examined whether subcortical structure mediated associations between lead risk and cognitive performance. Our analyses employed a cross-sectional analysis of baseline data from the observational Adolescent Brain Cognitive Development (ABCD) Study. The multi-center ABCD Study used school-based enrollment to recruit a demographically diverse cohort of almost 11,900 9- and 10-year-old children from an initial 22 study sites. The analyzed sample included data from 8,524 typically developing child participants and their parents or caregivers. The primary outcomes and measures were subcortical brain structure, cognitive performance using the National Institutes of Health Toolbox, and geocoded risk of lead exposure. Children who lived in neighborhoods with greater risks of environmental lead exposure exhibited smaller volumes of the mid-anterior (partial correlation coefficient [rp] = -0.040), central (rp = -0.038), and mid-posterior corpus callosum (rp = -0.035). Smaller volumes of these three callosal regions were associated with poorer performance on cognitive tests measuring language and processing speed. The association of lead exposure risk with cognitive performance was partially mediated through callosal volume, particularly the mid-posterior corpus callosum. In contrast, neighborhood-level indicators of disadvantage were not associated with smaller volumes of these brain structures. CONCLUSIONS Environmental factors related to the risk of lead exposure may be associated with certain aspects of cognitive functioning via diminished subcortical brain structure, including the anterior splenium (i.e., mid-posterior corpus callosum).
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Affiliation(s)
- Andrew T. Marshall
- Children’s Hospital Los Angeles, and the Department of Pediatrics, University of Southern California, Los Angeles, California, United States of America
| | - Rob McConnell
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Bruce P. Lanphear
- Faculty of Health Sciences, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Wesley K. Thompson
- Department of Biostatistics, Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, United States of America
| | - Megan M. Herting
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Elizabeth R. Sowell
- Children’s Hospital Los Angeles, and the Department of Pediatrics, University of Southern California, Los Angeles, California, United States of America
- * E-mail:
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15
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Shokri-Kojori E, Bennett IJ, Tomeldan ZA, Krawczyk DC, Rypma B. Estimates of brain age for gray matter and white matter in younger and older adults: Insights into human intelligence. Brain Res 2021; 1763:147431. [PMID: 33737067 PMCID: PMC8428193 DOI: 10.1016/j.brainres.2021.147431] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 02/01/2021] [Accepted: 03/10/2021] [Indexed: 12/18/2022]
Abstract
Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.
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Affiliation(s)
- Ehsan Shokri-Kojori
- Center for BrainHealth®, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA.
| | - Ilana J Bennett
- Center for BrainHealth®, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA; Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Zuri A Tomeldan
- Center for BrainHealth®, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Daniel C Krawczyk
- Center for BrainHealth®, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA; Department of Psychiatry, The University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA
| | - Bart Rypma
- Center for BrainHealth®, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA; Department of Psychiatry, The University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA
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16
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Girault JB, Cornea E, Goldman BD, Jha SC, Murphy VA, Li G, Wang L, Shen D, Knickmeyer RC, Styner M, Gilmore JH. Cortical Structure and Cognition in Infants and Toddlers. Cereb Cortex 2021; 30:786-800. [PMID: 31365070 DOI: 10.1093/cercor/bhz126] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 05/21/2019] [Accepted: 05/22/2019] [Indexed: 12/21/2022] Open
Abstract
Cortical structure has been consistently related to cognitive abilities in children and adults, yet we know little about how the cortex develops to support emergent cognition in infancy and toddlerhood when cortical thickness (CT) and surface area (SA) are maturing rapidly. In this report, we assessed how regional and global measures of CT and SA in a sample (N = 487) of healthy neonates, 1-year-olds, and 2-year-olds related to motor, language, visual reception, and general cognitive ability. We report novel findings that thicker cortices at ages 1 and 2 and larger SA at birth, age 1, and age 2 confer a cognitive advantage in infancy and toddlerhood. While several expected brain-cognition relationships were observed, overlapping cortical regions were also implicated across cognitive domains, suggesting that infancy marks a period of plasticity and refinement in cortical structure to support burgeoning motor, language, and cognitive abilities. CT may be a particularly important morphological indicator of ability, but its impact on cognition is relatively weak when compared with gestational age and maternal education. Findings suggest that prenatal and early postnatal cortical developments are important for cognition in infants and toddlers but should be considered in relation to other child and demographic factors.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Barbara D Goldman
- Department of Psychology & Neuroscience and FPG Child Development Institute, University of North Carolina, Chapel Hill, NC, USA
| | - Shaili C Jha
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Veronica A Murphy
- Neuroscience Curriculum, University of North Carolina, Chapel Hill, NC, USA
| | - Gang Li
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Li Wang
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dinggang Shen
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rebecca C Knickmeyer
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.,Department of Pediatrics and Human Development, Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, Michigan, USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.,Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
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17
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Moharramipour A, Kitazawa S. What Underlies a Greater Reversal in Tactile Temporal Order Judgment When the Hands Are Crossed? A Structural MRI Study. Cereb Cortex Commun 2021; 2:tgab025. [PMID: 34296170 PMCID: PMC8152922 DOI: 10.1093/texcom/tgab025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 03/31/2021] [Accepted: 03/31/2021] [Indexed: 02/02/2023] Open
Abstract
Our subjective temporal order of two successive tactile stimuli, delivered one to each hand, is often inverted when our hands are crossed. However, there is great variability among different individuals. We addressed the question of why some show almost complete reversal, but others show little reversal. To this end, we obtained structural magnetic resonance imaging data from 42 participants who also participated in the tactile temporal order judgment (TOJ) task. We extracted the cortical thickness and the convoluted surface area as cortical characteristics in 68 regions. We found that the participants with a thinner, larger, and more convoluted cerebral cortex in 10 regions, including the right pars-orbitalis, right and left postcentral gyri, left precuneus, left superior parietal lobule, right middle temporal gyrus, left superior temporal gyrus, right cuneus, left supramarginal gyrus, and right rostral middle frontal gyrus, showed a smaller degree of judgment reversal. In light of major theoretical accounts, we suggest that cortical elaboration in the aforementioned regions improve the crossed-hand TOJ performance through better integration of the tactile stimuli with the correct spatial representations in the left parietal regions, better representation of spatial information in the postcentral gyrus, or improvement of top-down inhibitory control by the right pars-orbitalis.
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Affiliation(s)
- Ali Moharramipour
- Dynamic Brain Network Laboratory, Graduate School of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan
| | - Shigeru Kitazawa
- Dynamic Brain Network Laboratory, Graduate School of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan
- Department of Brain Physiology, Graduate School of Medicine, Osaka University, Osaka 565-0871, Japan
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka University, Osaka 565-0871, Japan
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18
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Shishegar R, Pizzagalli F, Georgiou-Karistianis N, Egan GF, Jahanshad N, Johnston LA. A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets. Neuroimage 2021; 229:117751. [PMID: 33460799 DOI: 10.1016/j.neuroimage.2021.117751] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 12/22/2020] [Accepted: 01/07/2021] [Indexed: 10/22/2022] Open
Abstract
An accurate measure of the complexity of patterns of cortical folding or gyrification is necessary for understanding normal brain development and neurodevelopmental disorders. Conventional gyrification indices (GIs) are calculated based on surface curvature (curvature-based GI) or an outer hull surface of the cortex (outer surface-based GI). The latter is dependent on the definition of the outer hull surface and a corresponding function between surfaces. In the present study, we propose the Laplace Beltrami-based gyrification index (LB-GI). This is a new curvature-based local GI computed using the first three Laplace Beltrami eigenfunction level sets. As with outer surface-based GI methods, this method is based on the hypothesis that gyrification stems from a flat surface during development. However, instead of quantifying gyrification with reference to corresponding points on an outer hull surface, LB-GI quantifies the gyrification at each point on the cortical surface with reference to their surrounding gyral points, overcoming several shortcomings of existing methods. The LB-GI was applied to investigate the cortical maturation profile of the human brain from preschool to early adulthood using the PING database. The results revealed more detail in patterns of cortical folding than conventional curvature-based methods, especially on frontal and posterior tips of the brain, such as the frontal pole, lateral occipital, lateral cuneus, and lingual. Negative associations of cortical folding with age were observed at cortical regions, including bilateral lingual, lateral occipital, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results also indicated positive significant associations between age and the LB-GI of bilateral insula, the medial orbitofrontal, frontal pole and rostral anterior cingulate regions. It is anticipated that the LB-GI will be advantageous in providing further insights in the understanding of brain development and degeneration in large clinical neuroimaging studies.
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Affiliation(s)
- Rosita Shishegar
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia; The Australian e-Health Research Centre, CSIRO, Melbourne, Australia.
| | - Fabrizio Pizzagalli
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA; Department of Neurosciences, University of Turin, Italy
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Gary F Egan
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Leigh A Johnston
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia; Melbourne Brain Centre Imaging Unit, University of Melbourne, Melbourne, Australia
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19
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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.
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20
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Satary Dizaji A, Vieira BH, Khodaei MR, Ashrafi M, Parham E, Hosseinzadeh GA, Salmon CEG, Soltanianzadeh H. Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data. Basic Clin Neurosci 2021; 12:1-28. [PMID: 33995924 PMCID: PMC8114859 DOI: 10.32598/bcn.12.1.574.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 05/10/2020] [Accepted: 10/28/2020] [Indexed: 11/20/2022] Open
Abstract
Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans.This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and restingstate fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.
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Affiliation(s)
- Aslan Satary Dizaji
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Bruno Hebling Vieira
- Inbrain Lab, Department of Physics, FFCLRP, University of São Paulo, Ribeirao Preto, Brazil
| | - Mohmmad Reza Khodaei
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Mahnaz Ashrafi
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Elahe Parham
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Gholam Ali Hosseinzadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | | | - Hamid Soltanianzadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Radiology Image Analysis Laboratory, Henry Ford Health System, Detroit, USA
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21
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Dreszer J, Grochowski M, Lewandowska M, Nikadon J, Gorgol J, Bałaj B, Finc K, Duch W, Kałamała P, Chuderski A, Piotrowski T. Spatiotemporal complexity patterns of resting-state bioelectrical activity explain fluid intelligence: Sex matters. Hum Brain Mapp 2020; 41:4846-4865. [PMID: 32808732 PMCID: PMC7643359 DOI: 10.1002/hbm.25162] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 07/12/2020] [Accepted: 07/27/2020] [Indexed: 11/11/2022] Open
Abstract
Neural complexity is thought to be associated with efficient information processing but the exact nature of this relation remains unclear. Here, the relationship of fluid intelligence (gf) with the resting-state EEG (rsEEG) complexity over different timescales and different electrodes was investigated. A 6-min rsEEG blocks of eyes open were analyzed. The results of 119 subjects (57 men, mean age = 22.85 ± 2.84 years) were examined using multivariate multiscale sample entropy (mMSE) that quantifies changes in information richness of rsEEG in multiple data channels at fine and coarse timescales. gf factor was extracted from six intelligence tests. Partial least square regression analysis revealed that mainly predictors of the rsEEG complexity at coarse timescales in the frontoparietal network (FPN) and the temporo-parietal complexities at fine timescales were relevant to higher gf. Sex differently affected the relationship between fluid intelligence and EEG complexity at rest. In men, gf was mainly positively related to the complexity at coarse timescales in the FPN. Furthermore, at fine and coarse timescales positive relations in the parietal region were revealed. In women, positive relations with gf were mostly observed for the overall and the coarse complexity in the FPN, whereas negative associations with gf were found for the complexity at fine timescales in the parietal and centro-temporal region. These outcomes indicate that two separate time pathways (corresponding to fine and coarse timescales) used to characterize rsEEG complexity (expressed by mMSE features) are beneficial for effective information processing.
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Affiliation(s)
- Joanna Dreszer
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
- Faculty of Philosophy and Social SciencesInstitute of Psychology, Nicolaus Copernicus UniversityToruńPoland
| | - Marek Grochowski
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
- Department of Informatics, Faculty of Physics, Astronomy, and InformaticsNicolaus Copernicus UniversityToruńPoland
| | - Monika Lewandowska
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
- Faculty of Philosophy and Social SciencesInstitute of Psychology, Nicolaus Copernicus UniversityToruńPoland
| | - Jan Nikadon
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
| | - Joanna Gorgol
- Faculty of PsychologyUniversity of WarsawWarsawPoland
| | - Bibianna Bałaj
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
- Faculty of Philosophy and Social SciencesInstitute of Psychology, Nicolaus Copernicus UniversityToruńPoland
| | - Karolina Finc
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
| | - Włodzisław Duch
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
- Department of Informatics, Faculty of Physics, Astronomy, and InformaticsNicolaus Copernicus UniversityToruńPoland
| | - Patrycja Kałamała
- Department of Cognitive ScienceInstitute of Philosophy, Jagiellonian UniversityKrakowPoland
| | - Adam Chuderski
- Department of Cognitive ScienceInstitute of Philosophy, Jagiellonian UniversityKrakowPoland
| | - Tomasz Piotrowski
- Centre for Modern Interdisciplinary TechnologiesNicolaus Copernicus UniversityToruńPoland
- Department of Informatics, Faculty of Physics, Astronomy, and InformaticsNicolaus Copernicus UniversityToruńPoland
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22
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Jäncke L, Liem F, Merillat S. Are language skills related to structural features in Broca's and Wernicke's area? Eur J Neurosci 2020; 53:1124-1135. [PMID: 33179366 DOI: 10.1111/ejn.15038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 11/02/2020] [Accepted: 11/02/2020] [Indexed: 11/30/2022]
Abstract
This study used structural magnetic resonance imaging to examine whether specific anatomical features of Broca's and Wernicke's areas are related to language functions in typically developing older subjects with no specific language expertize. Data from 231 subjects from the Zurich LHAB-study are used for this study. For these subjects, we obtained several psychometric measures from which we calculated performance measures reflecting specific psychological functions (language comprehension, verbal fluency, perceptual speed, visual memory, recognition of regularities, and logical thinking). From the MRI measurements, we calculated the cortical thickness and cortical surface of Broca's and Wernicke's areas. Applying multiple regression analyses, we identified a moderately strong relationship between language comprehension and the brain metrics from Broca's and Wernicke's areas and showed that approximately 10% of the variance in language comprehension performance is explained by the linear combination of all perisylvian brain metrics. The other psychological functions (verbal fluency, perceptual speed, visual memory, recognition of regularities, and logical thinking) are not related to these brain metrics. Subsequent detailed analyses revealed that the cortical thickness of Wernicke's area, in particular, contributed most to this structure-function relationship. The better performance in the language comprehension tests was related to a thicker cortex in Wernicke's area. Thus, this study demonstrates a structure-function relationship between the anatomical features of the perisylvian language areas and language comprehension, suggesting that particular anatomical features are associated with better language performance.
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Affiliation(s)
- Lutz Jäncke
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland.,University Research Priority Program "Dynamic of Healthy Aging", University, Zurich, Switzerland.,Zurich Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Franz Liem
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland.,University Research Priority Program "Dynamic of Healthy Aging", University, Zurich, Switzerland
| | - Susan Merillat
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland.,University Research Priority Program "Dynamic of Healthy Aging", University, Zurich, Switzerland
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23
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Dryburgh E, McKenna S, Rekik I. Predicting full-scale and verbal intelligence scores from functional Connectomic data in individuals with autism Spectrum disorder. Brain Imaging Behav 2020; 14:1769-1778. [PMID: 31055763 PMCID: PMC7572331 DOI: 10.1007/s11682-019-00111-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Decoding how intelligence is engrained in the human brain construct is vital in the understanding of particular neurological disorders. While the majority of existing studies focus on characterizing intelligence in neurotypical (NT) brains, investigating how neural correlates of intelligence scores are altered by atypical neurodevelopmental disorders, such as Autism Spectrum Disorders (ASD), is almost absent. To help fill this gap, we use a connectome-based predictive model (CPM) to predict intelligence scores from functional connectome data, derived from resting-state functional magnetic resonance imaging (rsfMRI). The utilized model learns how to select the most significant positive and negative brain connections, independently, to predict the target intelligence scores in NT and ASD populations, respectively. In the first step, using leave-one-out cross-validation we train a linear regressor robust to outliers to identify functional brain connections that best predict the target intelligence score (p - value < 0.01). Next, for each training subject, positive (respectively negative) connections are summed to produce single-subject positive (respectively negative) summary values. These are then paired with the target training scores to train two linear regressors: (a) a positive model which maps each positive summary value to the subject score, and (b) a negative model which maps each negative summary value to the target score. In the testing stage, by selecting the same connections for the left-out testing subject, we compute their positive and negative summary values, which are then fed to the trained negative and positive models for predicting the target score. This framework was applied to NT and ASD populations independently to identify significant functional connections coding for full-scale and verbal intelligence quotients in the brain.
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Affiliation(s)
- Elizabeth Dryburgh
- BASIRA Lab, CVIP Group, Computing, School of Science and Engineering, University of Dundee, Dundee, UK
| | - Stephen McKenna
- CVIP Group, Computing, School of Science and Engineering, University of Dundee, Dundee, UK
| | - Islem Rekik
- BASIRA Lab, CVIP Group, Computing, School of Science and Engineering, University of Dundee, Dundee, UK.
- Faculty of Computer and Informatics, Istanbul Technical University, Istanbul, Turkey.
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24
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Songthawornpong N, Teasdale TW, Olesen MV, Pakkenberg B. Is There a Correlation Between the Number of Brain Cells and IQ? Cereb Cortex 2020; 31:650-657. [PMID: 32939536 PMCID: PMC7727338 DOI: 10.1093/cercor/bhaa249] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 07/07/2020] [Accepted: 07/23/2020] [Indexed: 01/23/2023] Open
Abstract
Our access to a unique material of postmortem brains obtained from decades of data collection enabled a stereological analysis of the neuron numbers and correlation of results with individual premorbid intelligence quotient (IQ) data. In our sample of 50 brains from men, we find that IQ does not correlate with the number of brain cells in the human neocortex and was only weakly correlated to brain weight. Our stereological examination extended to measures of several other parameters that might be of relevance to intelligence, including numbers of cerebral glial cells (astrocytes, oligodendrocytes, and microglia) and the volume of key areas in the gray and white matter and of the cerebral ventricles, also showing near-zero nonsignificant correlations to IQ.
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Affiliation(s)
- Nicharatch Songthawornpong
- Research Laboratory for Stereology and Neuroscience, Department of Neurology, Bispebjerg-Frederiksberg Hospital, DK-2400 Copenhagen, Denmark
| | - Thomas W Teasdale
- Department of Psychology, Faculty of Social Sciences, University of Copenhagen, DK-1353 Copenhagen, Denmark
| | - Mikkel V Olesen
- Research Laboratory for Stereology and Neuroscience, Department of Neurology, Bispebjerg-Frederiksberg Hospital, DK-2400 Copenhagen, Denmark
| | - Bente Pakkenberg
- Research Laboratory for Stereology and Neuroscience, Department of Neurology, Bispebjerg-Frederiksberg Hospital, DK-2400 Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark
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25
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Schmitz-Koep B, Bäuml JG, Menegaux A, Nuttall R, Zimmermann J, Schneider SC, Daamen M, Scheef L, Boecker H, Zimmer C, Gaser C, Wolke D, Bartmann P, Sorg C, Hedderich DM. Decreased cortical thickness mediates the relationship between premature birth and cognitive performance in adulthood. Hum Brain Mapp 2020; 41:4952-4963. [PMID: 32820839 PMCID: PMC7643384 DOI: 10.1002/hbm.25172] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 06/25/2020] [Accepted: 08/04/2020] [Indexed: 01/05/2023] Open
Abstract
Cortical thickness (CTh) reflects cortical properties such as dendritic complexity and synaptic density, which are not only vulnerable to developmental disturbances caused by premature birth but also highly relevant for cognitive performance. We tested the hypotheses whether CTh in young adults is altered after premature birth and whether these aberrations are relevant for general cognitive abilities. We investigated CTh based on brain structural magnetic resonance imaging and surface-based morphometry in a large and prospectively collected cohort of 101 very premature-born adults (<32 weeks of gestation and/or birth weight [BW] below 1,500 g) and 111 full-term controls at 26 years of age. Cognitive performance was assessed by full-scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale. CTh was reduced in frontal, parietal, and temporal associative cortices predominantly in the left hemisphere in premature-born adults compared to controls. We found a significant positive association of CTh with both gestational age and BW, particularly in the left hemisphere, and a significant negative association between CTh and intensity of neonatal treatment within limited regions bilaterally. Full-scale IQ and CTh in the left hemisphere were positively correlated. Furthermore, CTh in the left hemisphere acted as a mediator on the association between premature birth and full-scale IQ. Results provide evidence that premature born adults have widespread reduced CTh that is relevant for their general cognitive performance. Data suggest lasting reductions in cortical microstructure subserving CTh after premature birth.
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Affiliation(s)
- Benita Schmitz-Koep
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Josef G Bäuml
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Aurore Menegaux
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Rachel Nuttall
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Juliana Zimmermann
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sebastian C Schneider
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcel Daamen
- Functional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany.,Department of Neonatology, University Hospital Bonn, Bonn, Germany
| | - Lukas Scheef
- Functional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany
| | - Henning Boecker
- Functional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany
| | - Claus Zimmer
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry, University Hospital Jena, Jena, Germany.,Department of Neurology, University Hospital Jena, Jena, Germany
| | - Dieter Wolke
- Department of Psychology, University of Warwick, Coventry, UK.,Warwick Medical School, University of Warwick, Coventry, UK
| | - Peter Bartmann
- Department of Neonatology, University Hospital Bonn, Bonn, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Psychiatry, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dennis M Hedderich
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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26
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Sripada C, Angstadt M, Rutherford S, Taxali A, Shedden K. Toward a "treadmill test" for cognition: Improved prediction of general cognitive ability from the task activated brain. Hum Brain Mapp 2020; 41:3186-3197. [PMID: 32364670 PMCID: PMC7375130 DOI: 10.1002/hbm.25007] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 03/06/2020] [Accepted: 04/03/2020] [Indexed: 02/02/2023] Open
Abstract
General cognitive ability (GCA) refers to a trait-like ability that contributes to performance across diverse cognitive tasks. Identifying brain-based markers of GCA has been a longstanding goal of cognitive and clinical neuroscience. Recently, predictive modeling methods have emerged that build whole-brain, distributed neural signatures for phenotypes of interest. In this study, we employ a predictive modeling approach to predict GCA based on fMRI task activation patterns during the N-back working memory task as well as six other tasks in the Human Connectome Project dataset (n = 967), encompassing 15 task contrasts in total. We found tasks are a highly effective basis for prediction of GCA: The 2-back versus 0-back contrast achieved a 0.50 correlation with GCA scores in 10-fold cross-validation, and 13 out of 15 task contrasts afforded statistically significant prediction of GCA. Additionally, we found that task contrasts that produce greater frontoparietal activation and default mode network deactivation-a brain activation pattern associated with executive processing and higher cognitive demand-are more effective in the prediction of GCA. These results suggest a picture analogous to treadmill testing for cardiac function: Placing the brain in a more cognitively demanding task state significantly improves brain-based prediction of GCA.
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Affiliation(s)
- Chandra Sripada
- Department of PsychiatryUniversity of MichiganAnn ArborMichiganUSA
| | - Mike Angstadt
- Department of PsychiatryUniversity of MichiganAnn ArborMichiganUSA
| | - Saige Rutherford
- Department of PsychiatryUniversity of MichiganAnn ArborMichiganUSA
| | - Aman Taxali
- Department of PsychiatryUniversity of MichiganAnn ArborMichiganUSA
| | - Kerby Shedden
- Department of StatisticsUniversity of MichiganAnn ArborMichiganUSA
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27
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Ge T, Chen CY, Doyle AE, Vettermann R, Tuominen LJ, Holt DJ, Sabuncu MR, Smoller JW. The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology. Cereb Cortex 2020; 29:3471-3481. [PMID: 30272126 PMCID: PMC6644848 DOI: 10.1093/cercor/bhy216] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2018] [Revised: 07/20/2018] [Indexed: 01/03/2023] Open
Abstract
Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic, and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses relate the genetic overlap between cognitive ability and cortical thickness measurements to bilateral primary motor cortex as well as predominantly left superior temporal cortex and proximal regions. These findings extend our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.
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Affiliation(s)
- Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chia-Yen Chen
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alysa E Doyle
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Richard Vettermann
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Lauri J Tuominen
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Daphne J Holt
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Mert R Sabuncu
- School of Electrical and Computer Engineering and Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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28
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Association between diffusivity measures and language and cognitive-control abilities from early toddler’s age to childhood. Brain Struct Funct 2020; 225:1103-1122. [DOI: 10.1007/s00429-020-02062-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 03/20/2020] [Indexed: 12/20/2022]
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29
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Marshall AT, Betts S, Kan EC, McConnell R, Lanphear BP, Sowell ER. Association of lead-exposure risk and family income with childhood brain outcomes. Nat Med 2020; 26:91-97. [PMID: 31932788 PMCID: PMC6980739 DOI: 10.1038/s41591-019-0713-y] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 11/22/2019] [Indexed: 02/08/2023]
Abstract
Socioeconomic factors influence brain development and structure, but most studies have overlooked neurotoxic insults that impair development, such as lead exposure. Childhood lead exposure affects cognitive development at the lowest measurable concentrations, but little is known about its impact on brain development during childhood. We examined cross-sectional associations among brain structure, cognition, geocoded measures of the risk of lead exposure and sociodemographic characteristics in 9,712 9- and 10-year-old children. Here we show stronger negative associations of living in high-lead-risk census tracts in children from lower- versus higher-income families. With increasing risk of exposure, children from lower-income families exhibited lower cognitive test scores, smaller cortical volume and smaller cortical surface area. Reducing environmental insults associated with lead-exposure risk might confer greater benefit to children experiencing more environmental adversity, and further understanding of the factors associated with high lead-exposure risk will be critical for improving such outcomes in children.
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Affiliation(s)
- Andrew T Marshall
- Children's Hospital Los Angeles, and the Department of Pediatrics, University of Southern California, Los Angeles, CA, USA
| | - Samantha Betts
- Children's Hospital Los Angeles, and the Department of Pediatrics, University of Southern California, Los Angeles, CA, USA
| | - Eric C Kan
- Children's Hospital Los Angeles, and the Department of Pediatrics, University of Southern California, Los Angeles, CA, USA
| | - Rob McConnell
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Bruce P Lanphear
- Faculty of Health Sciences, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Elizabeth R Sowell
- Children's Hospital Los Angeles, and the Department of Pediatrics, University of Southern California, Los Angeles, CA, USA.
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30
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Belrose C, Duffaud A, Rakotoarison E, Faget C, Raynaud P, Dutheil F, Boyer L, Billaud JB, Trousselard M. Neurological Soft Signs and Post-Traumatic Stress Disorder: A Biomarker of Severity? Front Psychiatry 2020; 11:533662. [PMID: 33192652 PMCID: PMC7606651 DOI: 10.3389/fpsyt.2020.533662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 09/03/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The psychophysiological changes for individual suffering from chronic post-traumatic stress disorder (PTSD) raise to the questions of how facilitate recovery and return to work. Negative alterations in neuro-cognition remain a complaint for patients and participate to long-term functional impairments. Neurological soft signs (NSSs) appear as a candidate for better understanding these complaints. They have been reported in several mental disorders. They are found in several behavioral and/or neurocognitive disorders and are taken into account by psychiatric rehabilitation programs to support recovery. As few studies evaluate NSSs in PTSD, our exploratory study aims to assess NSSs in chronic PTSD and their relationships with PTSD severity. METHOD Twenty-two patients with a clinical diagnosis of chronic PTSD were evaluated in terms of PTSD severity (post-traumatic checklist scale, PCL5), NSSs (NSSs psychomotor skills scale, PASS), and well-being upon arrival to the hospital and compared with 15 healthy subjects. Statistical non-parametric analyses assessed the relationships between these variables. RESULTS PTSD subjects exhibited higher NSSs compared with healthy subjects. NSSs were positively associated with PTSD severity, with negative alterations in cognition and mood, and with impairment in well-being. They were higher in women compared with men. No impact of age was found. Three groups were identified based on the severity of the PTSD. Severe PTSD exhibited NSSs characterized by motor integration alterations. CONCLUSIONS This pilot study suggests that NSSs might be a biomarker of PTSD severity. This proof of concept highlights the need for further research for better evaluating the clinical neuro-functional impairment. This will be helping for defining neurological remediation for promoting PTSD recovery.
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Affiliation(s)
- Célia Belrose
- Département de Neurosciences et Sciences Cognitives, Unité de Neurophysiologie du Stress, Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France.,Réseau ABC des Psychotraumas, Montpellier, France.,APEMAC, EA 4360, Université de Lorraine, Nancy, France
| | - Anais Duffaud
- Département de Neurosciences et Sciences Cognitives, Unité de Neurophysiologie du Stress, Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France.,Réseau ABC des Psychotraumas, Montpellier, France
| | | | | | - Philippe Raynaud
- APEMAC, EA 4360, Université de Lorraine, Nancy, France.,Centre Hospitalier Léon Jean Grégory, Thuir, France
| | - Frédéric Dutheil
- Université Clermont Auvergne, CNRS, LaPSCo, Physiological and Psychosocial Stress, CHU Clermont-Ferrand, Clermont-Ferrand, France.,Faculty of Health, School of Exercise Science, Australian Catholic University, Melbourne, VIC, Australia
| | - Léa Boyer
- Département de Neurosciences et Sciences Cognitives, Unité de Neurophysiologie du Stress, Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France
| | - Jean-Baptiste Billaud
- Département de Neurosciences et Sciences Cognitives, Unité de Neurophysiologie du Stress, Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France
| | - Marion Trousselard
- Département de Neurosciences et Sciences Cognitives, Unité de Neurophysiologie du Stress, Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France.,Réseau ABC des Psychotraumas, Montpellier, France.,APEMAC, EA 4360, Université de Lorraine, Nancy, France
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31
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Jäncke L, Sele S, Liem F, Oschwald J, Merillat S. Brain aging and psychometric intelligence: a longitudinal study. Brain Struct Funct 2019; 225:519-536. [DOI: 10.1007/s00429-019-02005-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Accepted: 12/06/2019] [Indexed: 12/25/2022]
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32
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Zhao L, Matloff W, Ning K, Kim H, Dinov ID, Toga AW. Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults. Cereb Cortex 2019; 29:4169-4193. [PMID: 30535294 PMCID: PMC6931275 DOI: 10.1093/cercor/bhy300] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 11/05/2018] [Accepted: 11/07/2018] [Indexed: 12/11/2022] Open
Abstract
Brain structural morphology differs with age. This study examined age-differences in surface-based morphometric measures of cortical thickness, volume, and surface area in a well-defined sample of 8137 generally healthy UK Biobank participants aged 45-79 years. We illustrate that the complexity of age-related brain morphological differences may be related to the laminar organization and regional evolutionary history of the cortex, and age of about 60 is a break point for increasing negative associations between age and brain morphology in Alzheimer's disease (AD)-prone areas. We also report novel relationships of age-related cortical differences with individual factors of sex, cognitive functions of fluid intelligence, reaction time and prospective memory, cigarette smoking, alcohol consumption, sleep disruption, genetic markers of apolipoprotein E, brain-derived neurotrophic factor, catechol-O-methyltransferase, and several genome-wide association study loci for AD and further reveal joint effects of cognitive functions, lifestyle behaviors, and education on age-related cortical differences. These findings provide one of the most extensive characterizations of age associations with major brain morphological measures and improve our understanding of normal structural brain aging and its potential modifiers.
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Affiliation(s)
- Lu Zhao
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - William Matloff
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Kaida Ning
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Hosung Kim
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Ivo D Dinov
- Statistics Online Computational Resource, HBBS, University of Michigan, Ann Arbor, MI 48109-2003, USA
- Michigan Institute for Data Science, HBBS, University of Michigan, Ann Arbor, MI 48109-1042, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
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33
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Jäncke L, Liem F, Merillat S. Weak correlations between body height and several brain metrics in healthy elderly subjects. Eur J Neurosci 2019; 50:3578-3589. [DOI: 10.1111/ejn.14501] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Revised: 06/18/2019] [Accepted: 06/27/2019] [Indexed: 01/06/2023]
Affiliation(s)
- Lutz Jäncke
- Division Neuropsychology Institute of Psychology University of Zurich Zurich Switzerland
- University Research Priority Program (URPP) “Dynamics of Healthy Aging” University of Zurich Zurich Switzerland
| | - Franz Liem
- Division Neuropsychology Institute of Psychology University of Zurich Zurich Switzerland
- University Research Priority Program (URPP) “Dynamics of Healthy Aging” University of Zurich Zurich Switzerland
| | - Susan Merillat
- Division Neuropsychology Institute of Psychology University of Zurich Zurich Switzerland
- University Research Priority Program (URPP) “Dynamics of Healthy Aging” University of Zurich Zurich Switzerland
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34
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Lawlor-Savage L, Clark CM, Goghari VM. No evidence that working memory training alters gray matter structure: A MRI surface -based analysis. Behav Brain Res 2019; 360:323-340. [DOI: 10.1016/j.bbr.2018.12.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 11/09/2018] [Accepted: 12/03/2018] [Indexed: 01/05/2023]
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35
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Chen Y, Xue F. The impact of gestational hypothyroxinemia on the cognitive and motor development of offspring. J Matern Fetal Neonatal Med 2018; 33:1940-1945. [PMID: 30348031 DOI: 10.1080/14767058.2018.1529749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
In the past decade, it is still controversial whether gestational hypothyroxinemia has adverse effects on fetal brain development. Animal models of maternal hypothyroxinemia have proved that thyroid hormone is necessary for the adequate development of a number of neuropsychological abilities whereas the type of deficit depends on the timing of thyroid hormone (TH) deficiency. However, different from animal experiments, evidence from clinical trials showed that the major determinant of mental and motor function delay in offspring is the gestational age at onset of maternal hypothyroxinemia. The correlation between levels of maternal FT4 in the first trimester and impaired neurodevelopment in offspring is strongest. With the progress of pregnancy, the correlation weakened gradually and disappeared until late pregnancy. Only two studies involving randomized controlled trials have examined the treatment of hypothyroxinemia with levothyroxine in pregnancy. However, both randomized trials were started too late in gestation to have a major influence on brain development.
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Affiliation(s)
- Yuanyuan Chen
- Obstetrics and Gynecology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Fengxia Xue
- Obstetrics and Gynecology Department, Tianjin Medical University General Hospital, Tianjin, China
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36
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Alamiri B, Nelson C, Fitzmaurice GM, Murphy JM, Gilman SE. Neurological soft signs and cognitive performance in early childhood. Dev Psychol 2018; 54:2043-2052. [PMID: 30265034 DOI: 10.1037/dev0000566] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Neurological soft signs (NSSs), minor neurological abnormalities, have been implicated as risk factors for poor cognitive performance in small-scale studies. Here we investigate the associations between NSSs and multiple domains of cognitive performance in a large, population-based cohort and evaluate sex differences in these associations. We analyzed data from 35,710 seven-year-old children in the Collaborative Perinatal Project to study the association between the number of NSSs and cognitive test scores using multiple linear regression models adjusting for risk factors for brain injury and aberrant neurodevelopment. NSSs were associated with lower scores on all domains of cognitive performance. Each additional soft sign was associated with lower full-scale IQ (b = -4.83, 95% CI [-5.06, -4.60]), performance IQ (b = -4.28, 95% CI [-4.54, -4.02]), and verbal IQ scores (b = -4.53, 95% CI [-4.76, -4.30]), as well as arithmetic (b = -4.06, 95% CI [-4.26, -3.85]), spelling (b = -3.53, 95% CI [-3.75, -3.30]), and reading (b = -4.00, 95% CI [-4.26, -3.75]) scores on the Wide Range Achievement Test (WRAT). Only one sex difference was observed: The association between NSS and the WRAT spelling test was somewhat stronger in girls (b = -4.01, 95% CI [-4.26, -3.36]) than in boys (b = -3.53, 95% CI [-3.75, -3.30]). There is an association between NSSs and poor cognitive performance that is not attributable to established risk factors for brain injury and aberrant neurodevelopment. Further research is needed to investigate the mechanisms underlying this association and to determine if interventions targeting NSS in children might have beneficial effects on neurocognitive development. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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37
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Intrauterine growth restriction and development of the hippocampus: implications for learning and memory in children and adolescents. THE LANCET CHILD & ADOLESCENT HEALTH 2018; 2:755-764. [PMID: 30236384 DOI: 10.1016/s2352-4642(18)30245-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 07/13/2018] [Accepted: 07/20/2018] [Indexed: 12/15/2022]
Abstract
Intrauterine growth restriction (IUGR) is often the result of compromised placental function and suboptimal uteroplacental blood flow. Children born with IUGR have impaired cognitive functioning and specific memory deficits, indicating long-lasting impairments in hippocampal functioning; indeed, hippocampal volume is reduced in infants with IUGR. Animal studies have provided valuable insight into the nature of deficits in hippocampal-dependent functions observed in children born with IUGR; outcomes of experimental IUGR reveal reduced neuron numbers and morphological alterations in the cornu ammonis fields 1 and 3 and dentate gyrus subregions of the hippocampus. However, whether such early and ongoing structural changes in the hippocampus could account for deficits in spatial memory reported in adolescent rats with IUGR is yet to be established. Understanding the association between hippocampal structural and functional alterations in IUGR will aid in the development of interventions to minimise the effect of IUGR on the hippocampus and long-term cognitive outcomes.
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38
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Korevaar TIM, Tiemeier H, Peeters RP. Clinical associations of maternal thyroid function with foetal brain development: Epidemiological interpretation and overview of available evidence. Clin Endocrinol (Oxf) 2018; 89:129-138. [PMID: 29693263 DOI: 10.1111/cen.13724] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 04/16/2018] [Accepted: 04/17/2018] [Indexed: 01/13/2023]
Abstract
Thyroid hormone is an important regulator of early brain development, particularly during early stages of gestation during which foetal thyroid hormone availability depends on the maternal transfer of thyroid hormones. There is a wide range of experimental studies showing that low maternal thyroid hormone availability is associated with suboptimal brain development parameters. While few clinical studies have shown that overt maternal hypothyroidism is associated with lower child IQ, the question whether more subclinical changes in maternal thyroid function could also lead to suboptimal foetal brain development. In this review, we put the latter studies in perspective and discuss their interpretation from an epidemiological and clinical perspective. Furthermore, we extend this discussion to also include future perspective and identify important knowledge gaps in the field.
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Affiliation(s)
- Tim I M Korevaar
- Rotterdam Thyroid Center, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robin P Peeters
- Rotterdam Thyroid Center, Erasmus Medical Center, Rotterdam, The Netherlands
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39
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Chen R, Fall K, Czene K, Kennedy B, Valdimarsdóttir U, Fang F. Impact of parental cancer on IQ, stress resilience, and physical fitness in young men. Clin Epidemiol 2018; 10:593-604. [PMID: 29872348 PMCID: PMC5973433 DOI: 10.2147/clep.s152210] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Background A parental cancer diagnosis is a stressful life event, potentially leading to increased risks of mental and physical problems among children. This study aimed to investigate the associations of parental cancer with IQ, stress resilience, and physical fitness of the affected men during early adulthood. Materials and methods In this Swedish population-based study, we included 465,249 men born during 1973–1983 who underwent the military conscription examination around the age of 18 years. We identified cancer diagnoses among the parents of these men from the Cancer Register. IQ, stress resilience, and physical fitness of the men were assessed at the time of conscription and categorized into three levels: low, moderate, and high (reference category). We used multinomial logistic regression to assess the studied associations. Results Overall, parental cancer was associated with higher risks of low stress resilience (relative risk ratio [RRR]: 1.09 [95% confidence interval (CI) 1.04–1.15]) and low physical fitness (RRR: 1.12 [95% CI 1.05–1.19]). Stronger associations were observed for parental cancer with a poor expected prognosis (low stress resilience: RRR: 1.59 [95% CI 1.31–1.94]; low physical fitness: RRR: 1.45 [95% CI 1.14–1.85]) and for parental death after cancer diagnosis (low stress resilience: RRR: 1.29 [95% CI 1.16–1.43]; low physical fitness: RRR: 1.40 [95% CI 1.23–1.59]). Although there was no overall association between parental cancer and IQ, parental death after cancer diagnosis was associated with a higher risk of low IQ (RRR: 1.11 [95% CI 1.01–1.24]). Conclusion Parental cancer, particularly severe and fatal type, is associated with higher risks of low stress resilience and low physical fitness among men during early adulthood. Men who experienced parental death after cancer diagnosis also have a higher risk of low IQ.
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Affiliation(s)
- Ruoqing Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Katja Fall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Beatrice Kennedy
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Unnur Valdimarsdóttir
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.,Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Fang Fang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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40
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Kunz L, Reuter M, Axmacher N, Montag C. Conscientiousness is Negatively Associated with Grey Matter Volume in Young APOE ɛ4-Carriers. J Alzheimers Dis 2018; 56:1135-1144. [PMID: 28106551 DOI: 10.3233/jad-160854] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The etiology of late onset Alzheimer's disease (LOAD) depends on multiple factors, among which the APOE ɛ4 allele is the most adverse genetic determinant and conscientiousness represents an influential personality trait. A potential association of both factors with brain structure in young adulthood may constitute a constellation that sets the course toward or against the subtle disease progression of LOAD that starts decades before clinical manifestation. Hence, in the present study, we examined the modulating effects of APOE ɛ4 on the relation between personality dimensions, including conscientiousness, and total grey matter volume (GMV) in young healthy adults using an a priori genotyping design. 105 participants completed an inventory assessing the Five Factor Model of Personality (NEO-FFI) and a structural MRI scan. Total GMV was estimated using both Freesurfer as well as VBM8. Across all participants, total GMV was positively associated with extraversion and negatively related to age. In APOE ɛ4-carriers- but not in APOE ɛ4-non-carriers- conscientiousness was negatively associated with total GMV. In line with the hypothesis of antagonistic pleiotropy of the APOE ɛ4 allele, this result suggests that young APOE ɛ4-carriers with increased total GMV may particularly benefit from cognitive advantages and thus have a lower need to engage in conscientious behavior. In this subset of young APOE ɛ4-carriers, the reduction in conscientiousness could then bring along adverse health behavior in the long run, potentiating the risk for LOAD. Hence, young APOE ɛ4-carriers with increased total GMV may be at a particularly high risk for LOAD.
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Affiliation(s)
- Lukas Kunz
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Epileptology, University of Bonn, Bonn, Germany.,Department of Neuropsychology, Institute of Cognitive Neuroscience, Ruhr-University Bochum, Bochum, Germany
| | - Martin Reuter
- Department of Psychology, University of Bonn, Bonn, Germany.,Center for Economics and Neuroscience, University of Bonn, Bonn, Germany
| | - Nikolai Axmacher
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Epileptology, University of Bonn, Bonn, Germany.,Department of Neuropsychology, Institute of Cognitive Neuroscience, Ruhr-University Bochum, Bochum, Germany
| | - Christian Montag
- Institute for Psychology and Education, Ulm University, Ulm, Germany.,Key Laboratory for NeuroInformation/Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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41
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Chen Z, De Beuckelaer A, Wang X, Liu J. Distinct neural substrates of visuospatial and verbal-analytic reasoning as assessed by Raven's Advanced Progressive Matrices. Sci Rep 2017; 7:16230. [PMID: 29176725 PMCID: PMC5701148 DOI: 10.1038/s41598-017-16437-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 11/13/2017] [Indexed: 12/18/2022] Open
Abstract
Recent studies revealed spontaneous neural activity to be associated with fluid intelligence (gF) which is commonly assessed by Raven's Advanced Progressive Matrices, and embeds two types of reasoning: visuospatial and verbal-analytic reasoning. With resting-state fMRI data, using global brain connectivity (GBC) analysis which averages functional connectivity of a voxel in relation to all other voxels in the brain, distinct neural correlates of these two reasoning types were found. For visuospatial reasoning, negative correlations were observed in both the primary visual cortex (PVC) and the precuneus, and positive correlations were observed in the temporal lobe. For verbal-analytic reasoning, negative correlations were observed in the right inferior frontal gyrus (rIFG), dorsal anterior cingulate cortex and temporoparietal junction, and positive correlations were observed in the angular gyrus. Furthermore, an interaction between GBC value and type of reasoning was found in the PVC, rIFG and the temporal lobe. These findings suggest that visuospatial reasoning benefits more from elaborate perception to stimulus features, whereas verbal-analytic reasoning benefits more from feature integration and hypothesis testing. In sum, the present study offers, for different types of reasoning in gF, first empirical evidence of separate neural substrates in the resting brain.
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Affiliation(s)
- Zhencai Chen
- Department of Psychology, Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Alain De Beuckelaer
- Institute for Management Research, Radboud University, Nijmegen, The Netherlands
- Department of Personnel Management, Work and Organizational Psychology, Ghent University, Ghent, Belgium
| | - Xu Wang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Jia Liu
- Beijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, Beijing, China.
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42
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Westerhausen R, Friesen CM, Rohani DA, Krogsrud SK, Tamnes CK, Skranes JS, Håberg AK, Fjell AM, Walhovd KB. The corpus callosum as anatomical marker of intelligence? A critical examination in a large-scale developmental study. Brain Struct Funct 2017; 223:285-296. [PMID: 28801753 PMCID: PMC5772147 DOI: 10.1007/s00429-017-1493-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 08/04/2017] [Indexed: 12/14/2022]
Abstract
Intellectual abilities are supported by a large-scale fronto-parietal brain network distributed across both cerebral hemispheres. This bihemispheric network suggests a functional relevance of inter-hemispheric coordination, a notion which is supported by a series of recent structural magnetic resonance imaging (MRI) studies demonstrating correlations between intelligence scores (IQ) and corpus-callosum anatomy. However, these studies also reveal an age-related dissociation: mostly positive associations are reported in adult samples, while negative associations are found in developing samples. In the present study, we re-examine the association between corpus callosum and intelligence measures in a large (734 datasets from 495 participants) developmental mixed cross-sectional and longitudinal sample (6.4–21.9 years) using raw test scores rather than deviation IQ measures to account for the ongoing cognitive development in this age period. Analyzing mid-sagittal measures of regional callosal thickness, a positive association in the splenium of the corpus callosum was found for both verbal and performance raw test scores. This association was not present when the participants’ age was considered in the analysis. Thus, we did not reveal any association that cannot be explained by a temporal co-occurrence of overall developmental trends in intellectual abilities and corpus callosum maturation in the present developing sample.
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Affiliation(s)
- René Westerhausen
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway.
| | - Charline-Marie Friesen
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway
| | - Darius A Rohani
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway
| | - Stine K Krogsrud
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway
| | - Christian K Tamnes
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway
| | - Jon S Skranes
- Department of Laboratory Medicine, Children's and Women's Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Asta K Håberg
- Department of Medical Imaging, St. Olav's Hospital, Trondheim, Norway.,Department of Neuroscience, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Anders M Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Kristine B Walhovd
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Blindern, POB 1094, 0317, Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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43
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Mohan H, de Haan R, Mansvelder HD, de Kock CPJ. The posterior parietal cortex as integrative hub for whisker sensorimotor information. Neuroscience 2017. [PMID: 28642168 DOI: 10.1016/j.neuroscience.2017.06.020] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Our daily life consists of a continuous interplay between incoming sensory information and outgoing motor plans. Particularly during goal-directed behavior and active exploration of the sensory environment, brain circuits are merging sensory and motor signals. This is referred to as sensorimotor integration and is relevant for locomotion, vision or tactile exploration. The somatosensory (tactile) system is an attractive modality to study sensorimotor integration in health and disease, motivated by the need for revolutionary technology that builds upon conceptual understanding of sensorimotor integration, such as brain-machine-interfaces and neuro-prosthetics. In this perspective, we focus on the rat whisker system and put forward the posterior parietal cortex as a potential circuit where sensorimotor integration could occur during active somatosensation.
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Affiliation(s)
- Hemanth Mohan
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - Roel de Haan
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands.
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44
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Nikolaidis A, Baniqued PL, Kranz MB, Scavuzzo CJ, Barbey AK, Kramer AF, Larsen RJ. Multivariate Associations of Fluid Intelligence and NAA. Cereb Cortex 2017; 27:2607-2616. [PMID: 27005991 DOI: 10.1093/cercor/bhw070] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Understanding the neural and metabolic correlates of fluid intelligence not only aids scientists in characterizing cognitive processes involved in intelligence, but it also offers insight into intervention methods to improve fluid intelligence. Here we use magnetic resonance spectroscopic imaging (MRSI) to measure N-acetyl aspartate (NAA), a biochemical marker of neural energy production and efficiency. We use principal components analysis (PCA) to examine how the distribution of NAA in the frontal and parietal lobes relates to fluid intelligence. We find that a left lateralized frontal-parietal component predicts fluid intelligence, and it does so independently of brain size, another significant predictor of fluid intelligence. These results suggest that the left motor regions play a key role in the visualization and planning necessary for spatial cognition and reasoning, and we discuss these findings in the context of the Parieto-Frontal Integration Theory of intelligence.
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Affiliation(s)
- Aki Nikolaidis
- Beckman Institute for Advanced Science and Technology.,Neuroscience Program and
| | - Pauline L Baniqued
- Beckman Institute for Advanced Science and Technology.,Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Michael B Kranz
- Beckman Institute for Advanced Science and Technology.,Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Claire J Scavuzzo
- Neuroscience Program and.,Psychology Department, University of Alberta, Edmonton, Alberta, Canada
| | - Aron K Barbey
- Beckman Institute for Advanced Science and Technology
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology.,Neuroscience Program and.,Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ryan J Larsen
- Beckman Institute for Advanced Science and Technology
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45
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Cairó O. Assessing Relevance of External Cognitive Measures. Front Integr Neurosci 2017; 11:3. [PMID: 28270753 PMCID: PMC5319308 DOI: 10.3389/fnint.2017.00003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 02/07/2017] [Indexed: 12/03/2022] Open
Abstract
The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual.
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Affiliation(s)
- Osvaldo Cairó
- Department of Computer Science, Instituto Tecnológico Autónomo de México (ITAM) Mexico City, Mexico
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46
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Kang JS, Ojha A, Lee G, Lee M. Difference in brain activation patterns of individuals with high and low intelligence in linguistic and visuo-spatial tasks: An EEG study. INTELLIGENCE 2017. [DOI: 10.1016/j.intell.2017.01.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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47
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Fluid Intelligence and the Cross-Frequency Coupling of Neuronal Oscillations. SPANISH JOURNAL OF PSYCHOLOGY 2016; 19:E91. [PMID: 27919297 DOI: 10.1017/sjp.2016.86] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Several existing theoretical models predict that the individual capacity of working memory and abstract reasoning (fluid intelligence) strongly depends on certain features of neuronal oscillations, especially their cross-frequency coupling. Empirical evidence supporting these predictions is still scarce, but it makes the future studies on oscillatory coupling a promising line of research that can uncover the physiological underpinnings of fluid intelligence. Cross-frequency coupling may serve as the optimal level of description of neurocognitive processes, integrating their genetic, structural, neurochemical, and bioelectrical underlying factors with explanations in terms of cognitive operations driven by neuronal oscillations.
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48
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Making Brains run Faster: are they Becoming Smarter? SPANISH JOURNAL OF PSYCHOLOGY 2016; 19:E88. [DOI: 10.1017/sjp.2016.83] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
AbstractA brief overview of structural and functional brain characteristics related to g is presented in the light of major neurobiological theories of intelligence: Neural Efficiency, P-FIT and Multiple-Demand system. These theories provide a framework to discuss the main objective of the paper: what is the relationship between individual alpha frequency (IAF) and g? Three studies were conducted in order to investigate this relationship: two correlational studies and a third study in which we experimentally induced changes in IAF by means of transcranial alternating current stimulation (tACS). (1) In a large scale study (n = 417), no significant correlations between IAF and IQ were observed. However, in males IAF positively correlated with mental rotation and shape manipulation and with an attentional focus on detail. (2) The second study showed sex-specific correlations between IAF (obtained during task performance) and scope of attention in males and between IAF and reaction time in females. (3) In the third study, individuals’ IAF was increased with tACS. The induced changes in IAF had a disrupting effect on male performance on Raven’s matrices, whereas a mild positive effect was observed for females. Neuro-electric activity after verum tACS showed increased desynchronization in the upper alpha band and dissociation between fronto-parietal and right temporal brain areas during performance on Raven’s matrices. The results are discussed in the light of gender differences in brain structure and activity.
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49
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Van Schependom J, Jain S, Cambron M, Vanbinst AM, De Mey J, Smeets D, Nagels G. Reliability of measuring regional callosal atrophy in neurodegenerative diseases. NEUROIMAGE-CLINICAL 2016; 12:825-831. [PMID: 27830115 PMCID: PMC5094205 DOI: 10.1016/j.nicl.2016.10.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 10/13/2016] [Indexed: 11/21/2022]
Abstract
The Corpus Callosum (CC) is an important structure connecting the two brain hemispheres. As several neurodegenerative diseases are known to alter its shape, it is an interesting structure to assess as biomarker. Yet, currently, the CC-segmentation is often performed manually and is consequently an error prone and time-demanding procedure. In this paper, we present an accurate and automated method for corpus callosum segmentation based on T1-weighted MRI images. After the initial construction of a CC atlas based on healthy controls, a new image is subjected to a mid-sagittal plane (MSP) detection algorithm and a 3D affine registration in order to initialise the CC within the extracted MSP. Next, an active shape model is run to extract the CC. We calculated the reliability of most popular CC features (area, circularity, corpus callosum index and thickness profile) in healthy controls, Alzheimer's Disease patients and Multiple Sclerosis patients. Importantly, we also provide inter-scanner reliability estimates. We obtained an intra-class correlation coefficient (ICC) of over 0.95 for most features and most datasets. The inter-scanner reliability assessed on the MS patients was remarkably well and ranged from 0.77 to 0.97. In summary, we have constructed an algorithm that reliably detects the CC in 3D T1 images in a fully automated way in healthy controls and different neurodegenerative diseases. Although the CC area and the circularity are the most reliable features (ICC > 0.97); the reliability of the thickness profile (ICC > 0.90; excluding the tip) is sufficient to warrant its inclusion in future clinical studies. A completely automated segmentation of the Corpus Callosum Both traditional features and the thickness profile using Laplace's equation are calculated. Excellent reproducibility and accuracy in healthy controls Excellent reproducibility and accuracy in Alzheimer's Dementia and Multiple Sclerosis patients Excellent inter-scanner reliability enabling the pooling of multi-center data
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Affiliation(s)
- Jeroen Van Schependom
- Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium
| | - Saurabh Jain
- Icometrix NV, Kolonel Begaultlaan 1B, 3012 Leuven, Belgium
| | - Melissa Cambron
- Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium
| | - Anne-Marie Vanbinst
- Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium
| | - Johan De Mey
- Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium
| | - Dirk Smeets
- Icometrix NV, Kolonel Begaultlaan 1B, 3012 Leuven, Belgium
| | - Guy Nagels
- Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; Faculté de Psychologie et des Sciences de l'Education, Place du Parc 20, 7000 Mons, Belgium; National MS Center Melsbroek, Vanheylenstraat 16, 1820 Melsbroek, Belgium
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Paul EJ, Larsen RJ, Nikolaidis A, Ward N, Hillman CH, Cohen NJ, Kramer AF, Barbey AK. Dissociable brain biomarkers of fluid intelligence. Neuroimage 2016; 137:201-211. [DOI: 10.1016/j.neuroimage.2016.05.037] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2015] [Revised: 05/06/2016] [Accepted: 05/11/2016] [Indexed: 01/01/2023] Open
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