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Zhang L, Feng J, Liu C, Hu H, Zhou Y, Yang G, Peng X, Li T, Chen C, Xue G. Improved estimation of general cognitive ability and its neural correlates with a large battery of cognitive tasks. Cereb Cortex 2024; 34:bhad510. [PMID: 38183183 DOI: 10.1093/cercor/bhad510] [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: 10/21/2023] [Revised: 12/06/2023] [Accepted: 12/08/2023] [Indexed: 01/07/2024] Open
Abstract
Elucidating the neural mechanisms of general cognitive ability (GCA) is an important mission of cognitive neuroscience. Recent large-sample cohort studies measured GCA through multiple cognitive tasks and explored its neural basis, but they did not investigate how task number, factor models, and neural data type affect the estimation of GCA and its neural correlates. To address these issues, we tested 1,605 Chinese young adults with 19 cognitive tasks and Raven's Advanced Progressive Matrices (RAPM) and collected resting state and n-back task fMRI data from a subsample of 683 individuals. Results showed that GCA could be reliably estimated by multiple tasks. Increasing task number enhances both reliability and validity of GCA estimates and reliably strengthens their correlations with brain data. The Spearman model and hierarchical bifactor model yield similar GCA estimates. The bifactor model has better model fit and stronger correlation with RAPM but explains less variance and shows weaker correlations with brain data than does the Spearman model. Notably, the n-back task-based functional connectivity patterns outperform resting-state fMRI in predicting GCA. These results suggest that GCA derived from a multitude of cognitive tasks serves as a valid measure of general intelligence and that its neural correlates could be better characterized by task fMRI than resting-state fMRI data.
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Affiliation(s)
- Liang Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Junjiao Feng
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Chuqi Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Huinan Hu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Yu Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Gangyao Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Xiaojing Peng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Tong Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
| | - Chuansheng Chen
- Department of Psychological Science, University of California, Irvine, CA 92697, USA
| | - Gui Xue
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China
- Chinese Institute for Brain Research, Beijing 102206, PR China
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4
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Jiang C, He Y, Betzel RF, Wang YS, Xing XX, Zuo XN. Optimizing network neuroscience computation of individual differences in human spontaneous brain activity for test-retest reliability. Netw Neurosci 2023; 7:1080-1108. [PMID: 37781147 PMCID: PMC10473278 DOI: 10.1162/netn_a_00315] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 03/22/2023] [Indexed: 10/03/2023] Open
Abstract
A rapidly emerging application of network neuroscience in neuroimaging studies has provided useful tools to understand individual differences in intrinsic brain function by mapping spontaneous brain activity, namely intrinsic functional network neuroscience (ifNN). However, the variability of methodologies applied across the ifNN studies-with respect to node definition, edge construction, and graph measurements-makes it difficult to directly compare findings and also challenging for end users to select the optimal strategies for mapping individual differences in brain networks. Here, we aim to provide a benchmark for best ifNN practices by systematically comparing the measurement reliability of individual differences under different ifNN analytical strategies using the test-retest design of the Human Connectome Project. The results uncovered four essential principles to guide ifNN studies: (1) use a whole brain parcellation to define network nodes, including subcortical and cerebellar regions; (2) construct functional networks using spontaneous brain activity in multiple slow bands; and (3) optimize topological economy of networks at individual level; and (4) characterize information flow with specific metrics of integration and segregation. We built an interactive online resource of reliability assessments for future ifNN (https://ibraindata.com/research/ifNN).
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Affiliation(s)
- Chao Jiang
- School of Psychology, Capital Normal University, Beijing, China
| | - Ye He
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Richard F. Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - Yin-Shan Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, International Data Group/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiu-Xia Xing
- Department of Applied Mathematics, College of Mathematics, Faculty of Science, Beijing University of Technology, Beijing, China
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, International Data Group/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China
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5
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Tassone F, Protic D, Allen EG, Archibald AD, Baud A, Brown TW, Budimirovic DB, Cohen J, Dufour B, Eiges R, Elvassore N, Gabis LV, Grudzien SJ, Hall DA, Hessl D, Hogan A, Hunter JE, Jin P, Jiraanont P, Klusek J, Kooy RF, Kraan CM, Laterza C, Lee A, Lipworth K, Losh M, Loesch D, Lozano R, Mailick MR, Manolopoulos A, Martinez-Cerdeno V, McLennan Y, Miller RM, Montanaro FAM, Mosconi MW, Potter SN, Raspa M, Rivera SM, Shelly K, Todd PK, Tutak K, Wang JY, Wheeler A, Winarni TI, Zafarullah M, Hagerman RJ. Insight and Recommendations for Fragile X-Premutation-Associated Conditions from the Fifth International Conference on FMR1 Premutation. Cells 2023; 12:2330. [PMID: 37759552 PMCID: PMC10529056 DOI: 10.3390/cells12182330] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 09/09/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
The premutation of the fragile X messenger ribonucleoprotein 1 (FMR1) gene is characterized by an expansion of the CGG trinucleotide repeats (55 to 200 CGGs) in the 5' untranslated region and increased levels of FMR1 mRNA. Molecular mechanisms leading to fragile X-premutation-associated conditions (FXPAC) include cotranscriptional R-loop formations, FMR1 mRNA toxicity through both RNA gelation into nuclear foci and sequestration of various CGG-repeat-binding proteins, and the repeat-associated non-AUG (RAN)-initiated translation of potentially toxic proteins. Such molecular mechanisms contribute to subsequent consequences, including mitochondrial dysfunction and neuronal death. Clinically, premutation carriers may exhibit a wide range of symptoms and phenotypes. Any of the problems associated with the premutation can appropriately be called FXPAC. Fragile X-associated tremor/ataxia syndrome (FXTAS), fragile X-associated primary ovarian insufficiency (FXPOI), and fragile X-associated neuropsychiatric disorders (FXAND) can fall under FXPAC. Understanding the molecular and clinical aspects of the premutation of the FMR1 gene is crucial for the accurate diagnosis, genetic counseling, and appropriate management of affected individuals and families. This paper summarizes all the known problems associated with the premutation and documents the presentations and discussions that occurred at the International Premutation Conference, which took place in New Zealand in 2023.
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Affiliation(s)
- Flora Tassone
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Sacramento, CA 95817, USA;
- MIND Institute, University of California Davis, Davis, CA 95817, USA; (B.D.); (D.H.); (V.M.-C.)
| | - Dragana Protic
- Department of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Belgrade, 11129 Belgrade, Serbia;
- Fragile X Clinic, Special Hospital for Cerebral Palsy and Developmental Neurology, 11040 Belgrade, Serbia
| | - Emily Graves Allen
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA; (E.G.A.); (P.J.); (K.S.)
| | - Alison D. Archibald
- Victorian Clinical Genetics Services, Royal Children’s Hospital, Melbourne, VIC 3052, Australia;
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia;
- Genomics in Society Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Melbourne, VIC 3052, Australia
| | - Anna Baud
- Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Uniwersytetu Poznańskiego 6, 61-614 Poznan, Poland; (A.B.); (K.T.)
| | - Ted W. Brown
- Central Clinical School, University of Sydney, Sydney, NSW 2006, Australia;
- Fragile X Association of Australia, Brookvale, NSW 2100, Australia;
- NYS Institute for Basic Research in Developmental Disabilities, New York, NY 10314, USA
| | - Dejan B. Budimirovic
- Department of Psychiatry, Fragile X Clinic, Kennedy Krieger Institute, Baltimore, MD 21205, USA;
- Department of Psychiatry & Behavioral Sciences-Child Psychiatry, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Jonathan Cohen
- Fragile X Alliance Clinic, Melbourne, VIC 3161, Australia;
| | - Brett Dufour
- MIND Institute, University of California Davis, Davis, CA 95817, USA; (B.D.); (D.H.); (V.M.-C.)
- Department of Pathology and Laboratory Medicine, Institute for Pediatric Regenerative Medicine, Shriners Hospitals for Children of Northern California, School of Medicine, University of California Davis, Sacramento, CA 95817, USA;
| | - Rachel Eiges
- Stem Cell Research Laboratory, Medical Genetics Institute, Shaare Zedek Medical Center Affiliated with the Hebrew University School of Medicine, Jerusalem 91031, Israel;
| | - Nicola Elvassore
- Veneto Institute of Molecular Medicine (VIMM), 35129 Padova, Italy; (N.E.); (C.L.)
- Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
| | - Lidia V. Gabis
- Keshet Autism Center Maccabi Wolfson, Holon 5822012, Israel;
- Faculty of Medicine, Tel-Aviv University, Tel Aviv 6997801, Israel
| | - Samantha J. Grudzien
- Department of Neurology, University of Michigan, 4148 BSRB, 109 Zina Pitcher Place, Ann Arbor, MI 48109, USA; (S.J.G.); (P.K.T.)
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Deborah A. Hall
- Department of Neurological Sciences, Rush University, Chicago, IL 60612, USA;
| | - David Hessl
- MIND Institute, University of California Davis, Davis, CA 95817, USA; (B.D.); (D.H.); (V.M.-C.)
- Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California Davis, Sacramento, CA 95817, USA
| | - Abigail Hogan
- Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA; (A.H.); (J.K.)
| | - Jessica Ezzell Hunter
- RTI International, Research Triangle Park, NC 27709, USA; (J.E.H.); (S.N.P.); (M.R.); (A.W.)
| | - Peng Jin
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA; (E.G.A.); (P.J.); (K.S.)
| | - Poonnada Jiraanont
- Faculty of Medicine, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand;
| | - Jessica Klusek
- Department of Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA; (A.H.); (J.K.)
| | - R. Frank Kooy
- Department of Medical Genetics, University of Antwerp, 2000 Antwerp, Belgium;
| | - Claudine M. Kraan
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia;
- Diagnosis and Development, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
| | - Cecilia Laterza
- Veneto Institute of Molecular Medicine (VIMM), 35129 Padova, Italy; (N.E.); (C.L.)
- Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
| | - Andrea Lee
- Fragile X New Zealand, Nelson 7040, New Zealand;
| | - Karen Lipworth
- Fragile X Association of Australia, Brookvale, NSW 2100, Australia;
| | - Molly Losh
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL 60201, USA;
| | - Danuta Loesch
- School of Psychology and Public Health, La Trobe University, Melbourne, VIC 3086, Australia;
| | - Reymundo Lozano
- Departments of Genetics and Genomic Sciences and Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Marsha R. Mailick
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA;
| | - Apostolos Manolopoulos
- Intramural Research Program, Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD 21224, USA;
| | - Veronica Martinez-Cerdeno
- MIND Institute, University of California Davis, Davis, CA 95817, USA; (B.D.); (D.H.); (V.M.-C.)
- Department of Pathology and Laboratory Medicine, Institute for Pediatric Regenerative Medicine, Shriners Hospitals for Children of Northern California, School of Medicine, University of California Davis, Sacramento, CA 95817, USA;
| | - Yingratana McLennan
- Department of Pathology and Laboratory Medicine, Institute for Pediatric Regenerative Medicine, Shriners Hospitals for Children of Northern California, School of Medicine, University of California Davis, Sacramento, CA 95817, USA;
| | | | - Federica Alice Maria Montanaro
- Child and Adolescent Neuropsychiatry Unit, Department of Neuroscience, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy;
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, 70121 Bari, Italy
| | - Matthew W. Mosconi
- Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, KS 66045, USA;
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS 66045, USA
- Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS 66045, USA
| | - Sarah Nelson Potter
- RTI International, Research Triangle Park, NC 27709, USA; (J.E.H.); (S.N.P.); (M.R.); (A.W.)
| | - Melissa Raspa
- RTI International, Research Triangle Park, NC 27709, USA; (J.E.H.); (S.N.P.); (M.R.); (A.W.)
| | - Susan M. Rivera
- Department of Psychology, University of Maryland, College Park, MD 20742, USA;
| | - Katharine Shelly
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA; (E.G.A.); (P.J.); (K.S.)
| | - Peter K. Todd
- Department of Neurology, University of Michigan, 4148 BSRB, 109 Zina Pitcher Place, Ann Arbor, MI 48109, USA; (S.J.G.); (P.K.T.)
- Ann Arbor Veterans Administration Healthcare, Ann Arbor, MI 48105, USA
| | - Katarzyna Tutak
- Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Uniwersytetu Poznańskiego 6, 61-614 Poznan, Poland; (A.B.); (K.T.)
| | - Jun Yi Wang
- Center for Mind and Brain, University of California Davis, Davis, CA 95618, USA;
| | - Anne Wheeler
- RTI International, Research Triangle Park, NC 27709, USA; (J.E.H.); (S.N.P.); (M.R.); (A.W.)
| | - Tri Indah Winarni
- Center for Biomedical Research (CEBIOR), Faculty of Medicine, Universitas Diponegoro, Semarang 502754, Central Java, Indonesia;
| | - Marwa Zafarullah
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Sacramento, CA 95817, USA;
| | - Randi J. Hagerman
- MIND Institute, University of California Davis, Davis, CA 95817, USA; (B.D.); (D.H.); (V.M.-C.)
- Department of Pediatrics, School of Medicine, University of California Davis, Sacramento, CA 95817, USA
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8
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Boyle R, Connaughton M, McGlinchey E, Knight SP, De Looze C, Carey D, Stern Y, Robertson IH, Kenny RA, Whelan R. Connectome-based predictive modelling of cognitive reserve using task-based functional connectivity. Eur J Neurosci 2023; 57:490-510. [PMID: 36512321 PMCID: PMC10107737 DOI: 10.1111/ejn.15896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/07/2022] [Accepted: 12/08/2022] [Indexed: 12/14/2022]
Abstract
Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modelling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). This model generated summary measures of connectivity strength that accurately predicted a residual measure of cognitive reserve in unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.
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Affiliation(s)
- Rory Boyle
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Michael Connaughton
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Eimear McGlinchey
- School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Silvin P Knight
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Céline De Looze
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Daniel Carey
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York City, New York, USA
| | - Ian H Robertson
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Rose Anne Kenny
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
- Mercer's Institute for Successful Ageing, St. James's Hospital, Dublin, Ireland
| | - Robert Whelan
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
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