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Labonte AK, Camacho MC, Moser J, Koirala S, Laumann TO, Marek S, Fair D, Sylvester CM. Precision Functional Mapping to Advance Developmental Psychiatry Research. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100370. [PMID: 39309212 PMCID: PMC11416589 DOI: 10.1016/j.bpsgos.2024.100370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 07/22/2024] [Accepted: 07/25/2024] [Indexed: 09/25/2024] Open
Abstract
Many psychiatric conditions have their roots in early development. Individual differences in prenatal brain function (which is influenced by a combination of genetic risk and the prenatal environment) likely interact with individual differences in postnatal experience, resulting in substantial variation in brain functional organization and development in infancy. Neuroimaging has been a powerful tool for understanding typical and atypical brain function and holds promise for uncovering the neurodevelopmental basis of psychiatric illness; however, its clinical utility has been relatively limited thus far. A substantial challenge in this endeavor is the traditional approach of averaging brain data across groups despite individuals varying in their brain organization, which likely obscures important clinically relevant individual variation. Precision functional mapping (PFM) is a neuroimaging technique that allows the capture of individual-specific and highly reliable functional brain properties. Here, we discuss how PFM, through its focus on individuals, has provided novel insights for understanding brain organization across the life span and its promise in elucidating the neural basis of psychiatric disorders. We first summarize the extant literature on PFM in normative populations, followed by its limited utilization in studying psychiatric conditions in adults. We conclude by discussing the potential for infant PFM in advancing developmental precision psychiatry applications, given that many psychiatric disorders start during early infancy and are associated with changes in individual-specific functional neuroanatomy. By exploring the intersection of PFM, development, and psychiatric research, this article underscores the importance of individualized approaches in unraveling the complexities of brain function and improving clinical outcomes across development.
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Affiliation(s)
- Alyssa K. Labonte
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri
- Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, Missouri
| | - M. Catalina Camacho
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri
| | - Julia Moser
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota
| | - Sanju Koirala
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota
| | - Timothy O. Laumann
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri
| | - Scott Marek
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri
| | - Damien Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota
| | - Chad M. Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri
- Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, Missouri
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Tooley UA, Latham A, Kenley JK, Alexopoulos D, Smyser TA, Nielsen AN, Gorham L, Warner BB, Shimony JS, Neil JJ, Luby JL, Barch DM, Rogers CE, Smyser CD. Prenatal environment is associated with the pace of cortical network development over the first three years of life. Nat Commun 2024; 15:7932. [PMID: 39256419 PMCID: PMC11387486 DOI: 10.1038/s41467-024-52242-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 08/30/2024] [Indexed: 09/12/2024] Open
Abstract
Environmental influences on brain structure and function during early development have been well-characterized, but whether early environments are associated with the pace of brain development is not clear. In pre-registered analyses, we use flexible non-linear models to test the theory that prenatal disadvantage is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal disadvantage was assessed using a latent factor of socioeconomic disadvantage that included measures of mother's income-to-needs ratio, educational attainment, area deprivation index, insurance status, and nutrition. We find that prenatal disadvantage is associated with developmental increases in cortical network segregation, with neonates and toddlers with greater exposure to prenatal disadvantage showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between prenatal disadvantage and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. Disadvantage-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results shed light on associations between the early environment and trajectories of cortical development.
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Affiliation(s)
- Ursula A Tooley
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA.
| | - Aidan Latham
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Jeanette K Kenley
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Tara A Smyser
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Lisa Gorham
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA
| | - Joshua S Shimony
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Jeffrey J Neil
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Joan L Luby
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
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Buzi G, Eustache F, Droit-Volet S, Desaunay P, Hinault T. Towards a neurodevelopmental cognitive perspective of temporal processing. Commun Biol 2024; 7:987. [PMID: 39143328 PMCID: PMC11324894 DOI: 10.1038/s42003-024-06641-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 07/26/2024] [Indexed: 08/16/2024] Open
Abstract
The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.
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Affiliation(s)
- Giulia Buzi
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France
| | - Francis Eustache
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France
| | - Sylvie Droit-Volet
- Université Clermont Auvergne, LAPSCO, CNRS, UMR 6024, Clermont-Ferrand, France
| | - Pierre Desaunay
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France
- Service de Psychiatrie de l'enfant et de l'adolescent, CHU de Caen, Caen, France
| | - Thomas Hinault
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France.
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Vijayarajah S, Schlichting ML. Developmental refinements to neural attentional state during semantic memory retrieval through adolescence. Cortex 2024; 176:77-93. [PMID: 38761418 DOI: 10.1016/j.cortex.2024.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 02/25/2024] [Accepted: 04/16/2024] [Indexed: 05/20/2024]
Abstract
Despite the fact that attention undergoes protracted development, little is known about how it may support memory refinements in childhood and adolescence. Here, we asked whether people differentially focus their attention on semantic or perceptual information over development during memory retrieval. First, we trained a multivoxel classifier to characterize whole-brain neural patterns reflecting semantic versus perceptual attention in a cued attention task. We then used this classifier to quantify how attention varied in a separate dataset in which children, adolescents, and adults retrieved autobiographical, semantic, and episodic memories. All age groups demonstrated a semantic attentional bias during memory retrieval, with significant age differences in this bias during the semantic task. Trials began with a preparatory picture cue followed by a retrieval question, which allowed us to ask whether attentional biases varied by trial period. Adults showed a semantic bias earlier during the picture cues, whereas adolescents showed this bias during the question. Adults and adolescents also engaged different brain regions-superior parietal cortex and ventral visual regions, respectively-during preparatory picture cues. Our results demonstrate that retrieval-related attention undergoes refinement beyond childhood. These findings suggest that alongside expanding semantic knowledge, attention-related changes may support the maturation of factual knowledge retrieval.
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Hansen M, Simon KR, He X, Steele N, Thomas ML, Noble KG, Merz EC. Socioeconomic factors, sleep timing and duration, and amygdala resting-state functional connectivity in children. Front Psychiatry 2024; 15:1373546. [PMID: 38840942 PMCID: PMC11150855 DOI: 10.3389/fpsyt.2024.1373546] [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: 01/19/2024] [Accepted: 05/08/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Reduced sleep health has been consistently linked with increased negative emotion in children. While sleep characteristics have been associated with neural function in adults and adolescents, much less is known about these associations in children while considering socioeconomic context. In this study, we examined the associations among socioeconomic factors, sleep duration and timing, and resting-state functional connectivity (rsFC) of the amygdala in children. Methods Participants were typically-developing 5- to 9-year-olds from socioeconomically diverse families (61% female; N = 94). Parents reported on children's weekday and weekend bedtimes and wake-up times, which were used to compute sleep duration and midpoint. Analyses focused on amygdala-anterior cingulate cortex (ACC) connectivity followed by amygdala-whole brain connectivity. Results Lower family income-to-needs ratio and parental education were significantly associated with later weekday and weekend sleep timing and shorter weekday sleep duration. Shorter weekday sleep duration was associated with decreased amygdala-ACC and amygdala-insula connectivity. Later weekend sleep midpoint was associated with decreased amygdala-paracingulate cortex and amygdala-postcentral gyrus connectivity. Socioeconomic factors were indirectly associated with connectivity in these circuits via sleep duration and timing. Discussion These results suggest that socioeconomic disadvantage may interfere with both sleep duration and timing, in turn possibly altering amygdala connectivity in emotion processing and regulation circuits in children. Effective strategies supporting family economic conditions may have benefits for sleep health and brain development in children.
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Affiliation(s)
- Melissa Hansen
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Katrina R. Simon
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
| | - Xiaofu He
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
| | - Nick Steele
- Molecular, Cellular and Integrative Neuroscience, Colorado State University, Fort Collins, CO, United States
| | - Michael L. Thomas
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Kimberly G. Noble
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, United States
| | - Emily C. Merz
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
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Luo AC, Sydnor VJ, Pines A, Larsen B, Alexander-Bloch AF, Cieslak M, Covitz S, Chen AA, Esper NB, Feczko E, Franco AR, Gur RE, Gur RC, Houghton A, Hu F, Keller AS, Kiar G, Mehta K, Salum GA, Tapera T, Xu T, Zhao C, Salo T, Fair DA, Shinohara RT, Milham MP, Satterthwaite TD. Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy. Nat Commun 2024; 15:3511. [PMID: 38664387 PMCID: PMC11045762 DOI: 10.1038/s41467-024-47748-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.
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Affiliation(s)
- Audrey C Luo
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 55455, USA
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sydney Covitz
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Andrew A Chen
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, 29425, USA
| | | | - Eric Feczko
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
| | - Alexandre R Franco
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, 10962, USA
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, 10016, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Fengling Hu
- Penn Statistics in Imaging and Visualization Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Gregory Kiar
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
| | - Kahini Mehta
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Giovanni A Salum
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Tinashe Tapera
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, 02115, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
| | - Chenying Zhao
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Taylor Salo
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 55455, USA
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, 10962, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Auer T, Goldthorpe R, Peach R, Hebron H, Violante IR. Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function. Hum Brain Mapp 2024; 45:e26687. [PMID: 38651629 PMCID: PMC11036379 DOI: 10.1002/hbm.26687] [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: 09/14/2023] [Revised: 02/22/2024] [Accepted: 04/05/2024] [Indexed: 04/25/2024] Open
Abstract
The unprecedented increase in life expectancy presents a unique opportunity and the necessity to explore both healthy and pathological aspects of ageing. Electroencephalography (EEG) has been widely used to identify neuromarkers of cognitive ageing due to its affordability and richness in information. However, despite the growing volume of data and methodological advancements, the abundance of contradictory and non-reproducible findings has hindered clinical translation. To address these challenges, our study introduces a comprehensive workflow expanding on previous EEG studies and investigates various static and dynamic power and connectivity estimates as potential neuromarkers of cognitive ageing in a large dataset. We also assess the robustness of our findings by testing their susceptibility to band specification. Finally, we characterise our findings using functionally annotated brain networks to improve their interpretability and multi-modal integration. Our analysis demonstrates the effect of methodological choices on findings and that dynamic rather than static neuromarkers are not only more sensitive but also more robust. Consequently, they emerge as strong candidates for cognitive ageing neuromarkers. Moreover, we were able to replicate the most established EEG findings in cognitive ageing, such as alpha oscillation slowing, increased beta power, reduced reactivity across multiple bands, and decreased delta connectivity. Additionally, when considering individual variations in the alpha band, we clarified that alpha power is characteristic of memory performance rather than ageing, highlighting its potential as a neuromarker for cognitive ageing. Finally, our approach using functionally annotated source reconstruction allowed us to provide insights into domain-specific electrophysiological mechanisms underlying memory performance and ageing. HIGHLIGHTS: We provide an open and reproducible pipeline with a comprehensive workflow to investigate static and dynamic EEG neuromarkers. Neuromarkers related to neural dynamics are sensitive and robust. Individualised alpha power characterises cognitive performance rather than ageing. Functional annotation allows cross-modal interpretation of EEG findings.
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Affiliation(s)
- Tibor Auer
- School of PsychologyUniversity of SurreyGuildfordUK
| | | | | | - Henry Hebron
- School of PsychologyUniversity of SurreyGuildfordUK
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8
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Vin R, Blauch NM, Plaut DC, Behrmann M. Visual word processing engages a hierarchical, distributed, and bilateral cortical network. iScience 2024; 27:108809. [PMID: 38303718 PMCID: PMC10831251 DOI: 10.1016/j.isci.2024.108809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 02/03/2024] Open
Abstract
Although the Visual Word Form Area (VWFA) in left temporal cortex is considered the pre-eminent region in visual word processing, other regions are also implicated. We examined the entire text-selective circuit, using functional MRI. Ten regions of interest (ROIs) per hemisphere were defined, which, based on clustering, grouped into early vision, high-level vision, and language clusters. We analyzed the responses of the ROIs and clusters to words, inverted words, and consonant strings using univariate, multivariate, and functional connectivity measures. Bilateral modulation by stimulus condition was evident, with a stronger effect in left hemisphere regions. Last, using graph theory, we observed that the VWFA was equivalently connected with early visual and language clusters in both hemispheres, reflecting its role as a mediator in the circuit. Although the individual ROIs and clusters bilaterally were flexibly altered by the nature of the input, stability held at the level of global circuit connectivity, reflecting the complex hierarchical distributed system serving visual text perception.
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Affiliation(s)
- Raina Vin
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520, USA
| | - Nicholas M. Blauch
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Program in Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - David C. Plaut
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Marlene Behrmann
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15219, USA
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9
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Kiss O, Qu Z, Müller-Oehring EM, Baker FC, Mirzasoleiman B. Sleep, brain systems, and persistent stress in early adolescents during COVID-19: Insights from the ABCD study. J Affect Disord 2024; 346:234-241. [PMID: 37944709 PMCID: PMC10842722 DOI: 10.1016/j.jad.2023.10.158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/27/2023] [Accepted: 10/30/2023] [Indexed: 11/12/2023]
Abstract
PURPOSE The first year of the COVID-19 pandemic constituted a major life stress event for many adolescents, associated with disrupted school, behaviors, social networks, and health concerns. However, pandemic-related stress was not equivalent for everyone and could have been influenced by pre-pandemic factors including brain structure and sleep, which both undergo substantial development during adolescence. Here, we analyzed clusters of perceived stress levels across the pandemic and determined developmentally relevant pre-pandemic risk factors in brain structure and sleep of persistently high stress during the first year of the COVID-19 pandemic. METHODS We investigated longitudinal changes in perceived stress at six timepoints across the first year of the pandemic (May 2020-March 2021) in 5559 adolescents (50 % female; age range: 11-14 years) in the United States (U.S.) participating in the Adolescent Brain Cognitive Development (ABCD) study. In 3141 of these adolescents, we fitted machine learning models to identify the most important pre-pandemic predictors from structural MRI brain measures and self-reported sleep data that were associated with persistently high stress across the first year of the pandemic. RESULTS Patterns of perceived stress levels varied across the pandemic, with 5 % reporting persistently high stress. Our classifiers accurately detected persistently high stress (AUC > 0.7). Pre-pandemic brain structure, specifically cortical volume in temporal regions, and cortical thickness in multiple parietal and occipital regions, predicted persistent stress. Pre-pandemic sleep difficulties and short sleep duration were also strong predictors of persistent stress, along with more advanced pubertal stage. CONCLUSIONS Adolescents showed variable stress responses during the first year of the COVID-19 pandemic, and some reported persistently high stress across the whole first year. Vulnerability to persistent stress was evident in several brain structural and self-reported sleep measures, collected before the pandemic, suggesting the relevance of other pre-existing individual factors beyond pandemic-related factors, for persistently high stress responses.
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Affiliation(s)
- Orsolya Kiss
- Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA.
| | - Zihan Qu
- Electrical and Computer Engineering Department, University of California Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA
| | - Eva M Müller-Oehring
- Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA 94305, USA
| | - Fiona C Baker
- Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA; Brain Function Research Group, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
| | - Baharan Mirzasoleiman
- Computer Science Department, University of California Los Angeles, 404 Westwood Plaza, Los Angeles, CA 90095, USA
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10
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Michael C, Tillem S, Sripada CS, Burt SA, Klump KL, Hyde LW. Neighborhood poverty during childhood prospectively predicts adolescent functional brain network architecture. Dev Cogn Neurosci 2023; 64:101316. [PMID: 37857040 PMCID: PMC10587714 DOI: 10.1016/j.dcn.2023.101316] [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: 06/13/2023] [Revised: 09/14/2023] [Accepted: 10/13/2023] [Indexed: 10/21/2023] Open
Abstract
Family poverty has been associated with altered brain structure, function, and connectivity in youth. However, few studies have examined how disadvantage within the broader neighborhood may influence functional brain network organization. The present study leveraged a longitudinal community sample of 538 twins living in low-income neighborhoods to evaluate the prospective association between exposure to neighborhood poverty during childhood (6-10 y) with functional network architecture during adolescence (8-19 y). Using resting-state and task-based fMRI, we generated two latent measures that captured intrinsic brain organization across the whole-brain and network levels - network segregation and network segregation-integration balance. While age was positively associated with network segregation and network balance overall across the sample, these associations were moderated by exposure to neighborhood poverty. Specifically, these positive associations were observed only in youth from more, but not less, disadvantaged neighborhoods. Moreover, greater exposure to neighborhood poverty predicted reduced network segregation and network balance in early, but not middle or late, adolescence. These effects were detected both across the whole-brain system as well as specific functional networks, including fronto-parietal, default mode, salience, and subcortical systems. These findings indicate that where children live may exert long-reaching effects on the organization and development of the adolescent brain.
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Affiliation(s)
- Cleanthis Michael
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Scott Tillem
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Chandra S Sripada
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - S Alexandra Burt
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Kelly L Klump
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Luke W Hyde
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA; Survey Research Center at the Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
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11
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Prasanna A, Bajaj G, Anil MA, Bhat JS. A Delphi survey-based development and validation of cognitive-communication assessment tool for Indian preschoolers. Codas 2023; 36:e20220309. [PMID: 37909524 PMCID: PMC10727229 DOI: 10.1590/2317-1782/20232022309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/21/2023] [Indexed: 11/03/2023] Open
Abstract
PURPOSE To address the need for a standardized assessment tool for assessing cognitive-communication abilities among Indian preschoolers, the current study aimed at describing a Delphi based development and validation process for developing one such tool. The objectives of the research were to conceptualize and construct the tool, validate its content, and assess its feasibility through pilot testing. METHODS The study followed a Delphi approach to develop and validate the tool across four phases i.e. conceptualization; construction; content validation; and pilot testing. The first three phases were performed with a panel of six experts including speech-language pathologists and preschool teachers while the pilot testing was done with 20 typically developing preschoolers. A literature review was also conducted with the Delphi rounds to support the developmental process. RESULTS The first two rounds of the Delphi aided in the construction of a culturally and linguistically suitable story-based cognitive-communication assessment tool with the memory (free recall, recognition, and literary recall) and executive function (reasoning, inhibition, and switching) related tasks relevant for preschoolers. The content validation of the tool was continued with the experts till the revisions were satisfactory and yielded an optimum Content Validity Index. The pilot test of the finalized version confirmed its feasibility and appropriateness to assess developmental changes in the cognitive-communication abilities of preschoolers. CONCLUSION The study describes the Delphi-based conceptualization, construction, content validation, and feasibility check of a tool to assess cognitive-communication skills in preschool children.
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Affiliation(s)
- Aparna Prasanna
- Department of Audiology and Speech-Language Pathology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India.
| | - Gagan Bajaj
- Department of Audiology and Speech-Language Pathology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India.
| | - Malavika Anakkathil Anil
- The MARCS Institute of Brain, Behaviour and Development, Western Sydney University - Westmead, Australia.
| | - Jayashree S. Bhat
- Nitte Institute of Speech and Hearing - Mangalore, Karnataka, India.
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12
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Simpson-Kent IL, Gataviņš MM, Tooley UA, Boroshok AL, McDermott CL, Park AT, Delgado Reyes L, Bathelt J, Tisdall MD, Mackey AP. Multilayer network associations between the exposome and childhood brain development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.23.563611. [PMID: 37961103 PMCID: PMC10634748 DOI: 10.1101/2023.10.23.563611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Growing up in a high poverty neighborhood is associated with elevated risk for academic challenges and health problems. Here, we take a data-driven approach to exploring how measures of children's environments relate to the development of their brain structure and function in a community sample of children between the ages of 4 and 10 years. We constructed exposomes including measures of family socioeconomic status, children's exposure to adversity, and geocoded measures of neighborhood socioeconomic status, crime, and environmental toxins. We connected the exposome to two structural measures (cortical thickness and surface area, n = 170) and two functional measures (participation coefficient and clustering coefficient, n = 130). We found dense connections within exposome and brain layers and sparse connections between exposome and brain layers. Lower family income was associated with thinner visual cortex, consistent with the theory that accelerated development is detectable in early-developing regions. Greater neighborhood incidence of high blood lead levels was associated with greater segregation of the default mode network, consistent with evidence that toxins are deposited into the brain along the midline. Our study demonstrates the utility of multilayer network analysis to bridge environmental and neural explanatory levels to better understand the complexity of child development.
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Affiliation(s)
- Ivan L. Simpson-Kent
- Institute of Psychology, Developmental and Educational Psychology Unit, Leiden University, Leiden, the Netherlands
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Mārtiņš M. Gataviņš
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ursula A. Tooley
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Washington University in St. Louis, USA
- Department of Neurology, Washington University in St. Louis, USA
| | - Austin L. Boroshok
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Anne T. Park
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Joe Bathelt
- Department of Psychology, Royal Holloway, University of London, Egham, Surrey, United Kingdom
| | - M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Allyson P. Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
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13
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Tooley UA, Latham A, Kenley JK, Alexopoulos D, Smyser T, Warner BB, Shimony JS, Neil JJ, Luby JL, Barch DM, Rogers CE, Smyser CD. Prenatal environment is associated with the pace of cortical network development over the first three years of life. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.18.552639. [PMID: 37662189 PMCID: PMC10473645 DOI: 10.1101/2023.08.18.552639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Environmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.
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Affiliation(s)
- Ursula A. Tooley
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - Aidan Latham
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
| | - Jeanette K. Kenley
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
| | | | - Tara Smyser
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
| | - Barbara B. Warner
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110
| | - Joshua S. Shimony
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Jeffrey J. Neil
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
| | - Joan L. Luby
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
| | - Deanna M. Barch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110
| | - Cynthia E. Rogers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110
| | - Chris D. Smyser
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110
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14
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Boroshok AL, McDermott CL, Fotiadis P, Park AT, Tooley UA, Gataviņš MM, Tisdall MD, Bassett DS, Mackey AP. Individual differences in T1w/T2w ratio development during childhood. Dev Cogn Neurosci 2023; 62:101270. [PMID: 37348147 PMCID: PMC10439503 DOI: 10.1016/j.dcn.2023.101270] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 06/24/2023] Open
Abstract
Myelination is a key developmental process that promotes rapid and efficient information transfer. Myelin also stabilizes existing brain networks and thus may constrain neuroplasticity, defined here as the brain's potential to change in response to experiences rather than the canonical definition as the process of change. Characterizing individual differences in neuroplasticity may shed light on mechanisms by which early experiences shape learning, brain and body development, and response to interventions. The T1-weighted/T2-weighted (T1w/T2w) MRI signal ratio is a proxy measure of cortical microstructure and thus neuroplasticity. Here, in pre-registered analyses, we investigated individual differences in T1w/T2w ratios in children (ages 4-10, n = 157). T1w/T2w ratios were positively associated with age within early-developing sensorimotor and attention regions. We also tested whether socioeconomic status, cognition (crystallized knowledge or fluid reasoning), and biological age (as measured with molar eruption) were related to T1w/T2w signal but found no significant effects. Associations among T1w/T2w ratios, early experiences, and cognition may emerge later in adolescence and may not be strong enough to detect in moderate sample sizes.
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Affiliation(s)
- Austin L Boroshok
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
| | | | - Panagiotis Fotiadis
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Anne T Park
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ursula A Tooley
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Washington University in St. Louis, USA; Department of Neurology, Washington University in St. Louis, USA
| | - Mārtiņš M Gataviņš
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Santa Fe Institute, Santa Fe, NM, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
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15
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Ibbotson P. The Development of Executive Function: Mechanisms of Change and Functional Pressures. JOURNAL OF COGNITION AND DEVELOPMENT 2023. [DOI: 10.1080/15248372.2022.2160719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Paul Ibbotson
- School of Education, Childhood, Youth and Sport, The Open University, Milton Keynes, UK
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