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Zhang S, Jiang L, Hu Z, Liu W, Yu H, Chu Y, Wang J, Chen Y. T1w/T2w ratio maps identify children with autism spectrum disorder and the relationships between myelin-related changes and symptoms. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111040. [PMID: 38806093 DOI: 10.1016/j.pnpbp.2024.111040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 05/14/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Modern neuroimaging methods have revealed that autistic symptoms are associated with abnormalities in brain morphology, connectivity, and activity patterns. However, the changes in brain microstructure underlying the neurobiological and behavioral deficits of autism remain largely unknown. METHODS we characterized the associated abnormalities in intracortical myelination pattern by constructing cortical T1-weighted/T2-weighted ratio maps. Voxel-wise comparisons of cortical myelination were conducted between 150 children with autism spectrum disorder (ASD) and 139 typically developing (TD) children. Group differences in cortical T1-weighted/T2-weighted ratio and gray matter volume were then examined for associations with autistic symptoms. A convolutional neural network (CNN) model was also constructed to examine the utility of these regional abnormalities in cortical myelination for ASD diagnosis. RESULTS Compared to TD children, the ASD group exhibited widespread reductions in cortical myelination within regions related to default mode, salience, and executive control networks such as the inferior frontal gyrus, bilateral insula, left fusiform gyrus, bilateral hippocampus, right calcarine sulcus, bilateral precentral, and left posterior cingulate gyrus. Moreover, greater myelination deficits in most of these regions were associated with more severe autistic symptoms. In addition, children with ASD exhibited reduced myelination in regions with greater gray matter volume, including left insula, left cerebellum_4_5, left posterior cingulate gyrus, and right calcarine sulcus. Notably, the CNN model based on brain regions with abnormal myelination demonstrated high diagnostic efficacy for ASD. CONCLUSIONS Our findings suggest that microstructural abnormalities in myelination contribute to autistic symptoms and so are potentially promising therapeutic targets as well as biomarkers for ASD diagnosis.
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Affiliation(s)
- Shujun Zhang
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Liping Jiang
- Department of Pharmacy, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Zhe Hu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Wenjing Liu
- Children Rehabilitation Center, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Hao Yu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Yao Chu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Jiehuan Wang
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China.
| | - Yueqin Chen
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China.
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Hanson JL, Kahhalé I, Sen S. Integrating data science and neuroscience in developmental psychopathology: Formative examples and future directions. Dev Psychopathol 2024:1-8. [PMID: 38769837 DOI: 10.1017/s0954579424001056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
This commentary discusses opportunities for advancing the field of developmental psychopathology through the integration of data science and neuroscience approaches. We first review elements of our research program investigating how early life adversity shapes neurodevelopment and may convey risk for psychopathology. We then illustrate three ways that data science techniques (e.g., machine learning) can support developmental psychopathology research, such as by distinguishing between common and diverse developmental outcomes after stress exposure. Finally, we discuss logistical and conceptual refinements that may aid the field moving forward. Throughout the piece, we underscore the profound impact of Dr Dante Cicchetti, reflecting on how his work influenced our own, and gave rise to the field of developmental psychopathology.
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Affiliation(s)
- Jamie L Hanson
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Learning Research & Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Isabella Kahhalé
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Learning Research & Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sriparna Sen
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Learning Research & Development Center, University of Pittsburgh, Pittsburgh, PA, USA
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Perino MT, Sylvester CM, Rogers CE, Luby JL, Barch DM. Neighborhood Resource Deprivation as a Predictor of Bullying Perpetration and Resource-Driven Conduct Symptoms. J Am Acad Child Adolesc Psychiatry 2024:S0890-8567(24)00137-0. [PMID: 38522614 DOI: 10.1016/j.jaac.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 02/11/2024] [Accepted: 03/15/2024] [Indexed: 03/26/2024]
Abstract
OBJECTIVE Resource deprivation is linked to systemic factors that disproportionately impact historically marginalized communities, and theoretical work suggests that resource deprivation may increase risk for bullying behaviors. Bullying perpetration is an intransigent social problem and an early risk factor that perpetuates the school-to-prison pipeline. This study explored how resource deprivation (family- and neighborhood-level metrics) was associated with early childhood bullying behaviors and clinician-rated symptoms of psychopathology, while accounting for other known risk factors (early life stressors, traumatic events, parental arrest, domestic violence). METHOD Participants (306 children, mean age = 4.45 years) were enrolled in a longitudinal study (Preschool Depression Study) where demographics, clinician-rated assessments of psychopathology, and parent reports of social functioning were collected. Measures of bullying behaviors (bullying perpetration, generalized aggression, and victimization) were constructed. A cross-sectional approach was employed, and analyses examined the interrelations between race, bullying-related behaviors, resource deprivation, and psychopathology, while accounting for confounding variables, at the baseline assessment time point. RESULTS The bullying measure showed acceptable model fit (comparative fit index = 0.956, Tucker-Lewis index = 0.945, root mean square error of approximation = 0.061, standardized root mean residual = 0.052, normed χ2 ratio = 2). Neighborhood resource deprivation was more strongly associated with bullying perpetration (r = 0.324, p < .001) than generalized aggression (r = 0.236, Williams t303 = 2.11, p = .036) and remained significant when controlling for other known risk factors (parental arrests, domestic violence, stressors, traumas) and demographic factors. Bullying perpetration was linked with racial category, but the relation was fully mediated by neighborhood resource deprivation. Linear regression including bullying behaviors and symptoms of clinical psychopathology suggested that resource deprivation specifically led to increases in bullying perpetration (t = 2.831, p = .005) and clinician-rated symptoms of conduct disorder (t = 2.827, p = .005), which were attributable to increased rates of resource-driven conduct symptoms (bullies, lies to obtain goods, stolen without confrontation). CONCLUSION Resource deprivation is strongly and specifically associated with increases in bullying perpetration. Children growing up in impoverished neighborhoods show significant increases in resource-driven conduct behaviors, yet interventions often target individual-level factors. These results highlight the need to target social inequity to reduce bullying perpetration and suggest that interventions targeting neighborhoods should be tested to reduce bullying in early childhood. DIVERSITY & INCLUSION STATEMENT We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. One or more of the authors of this paper received support from a program designed to increase minority representation in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as living with a disability. We actively worked to promote sex and gender balance in our author group. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list.
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Affiliation(s)
- Michael T Perino
- Washington University School of Medicine in St. Louis, St. Louis, Missouri.
| | - Chad M Sylvester
- Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Cynthia E Rogers
- Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Joan L Luby
- Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Deanna M Barch
- Washington University School of Medicine in St. Louis, St. Louis, Missouri; Washington University in St. Louis, St. Louis, Missouri
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Langensee L, Rumetshofer T, Mårtensson J. Interplay of socioeconomic status, cognition, and school performance in the ABCD sample. NPJ SCIENCE OF LEARNING 2024; 9:17. [PMID: 38467686 PMCID: PMC10928106 DOI: 10.1038/s41539-024-00233-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 02/29/2024] [Indexed: 03/13/2024]
Abstract
Coming from a disadvantaged background can have negative impact on an individual's educational trajectory. Some people however seem unaffected and cope well with the demands and challenges posed by school education, despite growing up in adverse conditions, a phenomenon termed academic resilience. While it is uncertain which underlying factors make some people more likely to circumvent unfavorable odds than others, both socioeconomic status (SES) and cognitive ability have robustly been linked to school performance. The objective of the present work is to investigate if individual cognitive abilities and SES interact in their effect on grades. For this purpose, we analyzed SES, cognitive, and school performance data from 5001 participants from the Adolescent Brain Cognitive Development (ABCD) Study. Ordinal logistic regression models suggest similar patterns of associations between three SES measures (parental education, income-to-needs ratio, and neighborhood deprivation) and grades at two timepoints, with no evidence for interaction effects between SES and time. Parental education and income-to-needs ratio were associated with grades at both timepoints, irrespective of whether cognitive abilities were modeled or not. Neighborhood deprivation, in contrast, was only a statistically significant predictor of reported grades when cognitive abilities were not factored in. Cognitive abilities interacted with parental education level, meaning that they could be a safeguard against effects of SES on school performance.
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Affiliation(s)
- Lara Langensee
- Department of Clinical Sciences Lund, Division of Logopedics, Phoniatrics and Audiology, Lund University, Scania, Sweden.
| | - Theodor Rumetshofer
- Department of Clinical Sciences Lund, Division of Logopedics, Phoniatrics and Audiology, Lund University, Scania, Sweden
| | - Johan Mårtensson
- Department of Clinical Sciences Lund, Division of Logopedics, Phoniatrics and Audiology, Lund University, Scania, Sweden
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Norbom LB, Rokicki J, Eilertsen EM, Wiker T, Hanson J, Dahl A, Alnæs D, Fernández‐Cabello S, Beck D, Agartz I, Andreassen OA, Westlye LT, Tamnes CK. Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years. JCPP ADVANCES 2024; 4:e12220. [PMID: 38486948 PMCID: PMC10933599 DOI: 10.1002/jcv2.12220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/21/2023] [Indexed: 03/17/2024] Open
Abstract
Background A child's socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses of standard cortical morphometry that downplay the probable scenario where numerous biological pathways in sum account for SES-related cortical differences in youth. Methods To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study®, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology. Results Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC. Conclusion Structural brain MRI is sensitive to SES diversity in childhood, with GWC emerging as a particularly relevant marker together with surface area. In low-income families, having a more developed cortex across MRI metrics, appears beneficial for mental health.
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Affiliation(s)
- Linn B. Norbom
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
| | - Jaroslav Rokicki
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Centre of Research and Education in Forensic PsychiatryOslo University HospitalOsloNorway
| | - Espen M. Eilertsen
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
| | - Thea Wiker
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Jamie Hanson
- Learning Research and Development Center University of PittsburghPennsylvaniaPittsburghUSA
- Department of PsychologyUniversity of PittsburghPennsylvaniaPittsburghUSA
| | - Andreas Dahl
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Dag Alnæs
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyPedagogy and LawKristiania University CollegeOsloNorway
| | | | - Dani Beck
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Ingrid Agartz
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- Centre for Psychiatry ResearchDepartment of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care ServicesStockholmSweden
| | - Ole A. Andreassen
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Christian K. Tamnes
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
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Weissman DG, Baum GL, Sanders A, Rosen ML, Barch DM, McLaughlin KA, Somerville LH. Family income is not significantly associated with T1w/T2w ratio in the Human Connectome Project in Development. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2023; 1:10.1162/imag_a_00021. [PMID: 39006919 PMCID: PMC11242614 DOI: 10.1162/imag_a_00021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Growing evidence indicates that brain development varies as a function of family socioeconomic status (SES). Numerous studies have demonstrated that children from low-SES backgrounds have thinner cortex than children from higher-SES backgrounds. A recent study in a large developmental sample found widespread associations between lower SES and greater cortical T1w/T2w ratio-thought to be an indirect proxy for cortical myelin. We evaluated the association of family income with cortical T1w/T2w ratio as a function of age in the Human Connectome Project in Development sample of 989 youth aged 8-21 years. We observed no associations between family income and T1w/T2w ratio that were significant after corrections for multiple comparisons at the region, network, or whole-brain level. Region of practical equivalence (ROPE) analyses were also consistent with the absence of an association between family income and T1w/T2w ratio. We discuss potential methodological sources of inconsistency between this and the previous study examining the same question. While the question of whether family income may influence cortical myelin development remains, these null results may indicate that the association between SES and cortical myelin development may not be as strong as with other aspects of brain structure.
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Affiliation(s)
- David G. Weissman
- Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Graham L. Baum
- Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Ashley Sanders
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
| | - Maya L. Rosen
- Program in Neuroscience, Smith College, Northampton, MA, United States
| | - Deanna M. Barch
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
| | | | - Leah H. Somerville
- Department of Psychology, Harvard University, Cambridge, MA, United States
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Kilpatrick LA, Zhang K, Dong TS, Gee GC, Beltran-Sanchez H, Wang M, Labus JS, Naliboff BD, Mayer EA, Gupta A. Mediation of the association between disadvantaged neighborhoods and cortical microstructure by body mass index. COMMUNICATIONS MEDICINE 2023; 3:122. [PMID: 37714947 PMCID: PMC10504354 DOI: 10.1038/s43856-023-00350-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/21/2023] [Indexed: 09/17/2023] Open
Abstract
BACKGROUND Living in a disadvantaged neighborhood is associated with worse health outcomes, including brain health, yet the underlying biological mechanisms are incompletely understood. We investigated the relationship between neighborhood disadvantage and cortical microstructure, assessed as the T1-weighted/T2-weighted ratio (T1w/T2w) on magnetic resonance imaging, and the potential mediating roles of body mass index (BMI) and stress, as well as the relationship between trans-fatty acid intake and cortical microstructure. METHODS Participants comprised 92 adults (27 men; 65 women) who underwent neuroimaging and provided residential address information. Neighborhood disadvantage was assessed as the 2020 California State area deprivation index (ADI). The T1w/T2w ratio was calculated at four cortical ribbon levels (deep, lower-middle, upper-middle, and superficial). Perceived stress and BMI were assessed as potential mediating factors. Dietary data was collected in 81 participants. RESULTS Here, we show that worse ADI is positively correlated with BMI (r = 0.27, p = .01) and perceived stress (r = 0.22, p = .04); decreased T1w/T2w ratio in middle/deep cortex in supramarginal, temporal, and primary motor regions (p < .001); and increased T1w/T2w ratio in superficial cortex in medial prefrontal and cingulate regions (p < .001). Increased BMI partially mediates the relationship between worse ADI and observed T1w/T2w ratio increases (p = .02). Further, trans-fatty acid intake (high in fried fast foods and obesogenic) is correlated with these T1w/T2w ratio increases (p = .03). CONCLUSIONS Obesogenic aspects of neighborhood disadvantage, including poor dietary quality, may disrupt information processing flexibility in regions involved in reward, emotion regulation, and cognition. These data further suggest ramifications of living in a disadvantaged neighborhood on brain health.
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Affiliation(s)
- Lisa A Kilpatrick
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA.
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA.
| | - Keying Zhang
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
| | - Tien S Dong
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
- Division of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Gilbert C Gee
- Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, USA
- California Center for Population Research, University of California, Los Angeles, CA, USA
| | - Hiram Beltran-Sanchez
- Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, USA
- California Center for Population Research, University of California, Los Angeles, CA, USA
| | - May Wang
- Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Jennifer S Labus
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
| | - Bruce D Naliboff
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
| | - Emeran A Mayer
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
| | - Arpana Gupta
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA.
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA.
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Feijó DM, Pires JF, Gomes RMR, Carlo EJF, Viana TNDL, Magalhães JR, Santos ACT, Rodrigues LD, Oliveira LF, dos Santos JCC. The impact of child poverty on brain development: does money matter? Dement Neuropsychol 2023; 17:e20220105. [PMID: 37577181 PMCID: PMC10417148 DOI: 10.1590/1980-5764-dn-2022-0105] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 04/15/2023] [Accepted: 05/17/2023] [Indexed: 08/15/2023] Open
Abstract
The development of the human nervous system makes up a series of fundamental and interdependent events involving birth, growth, and neuronal maturation, in addition to the positive or negative selection of synapses of these neurons that will participate in the composition of neural circuits essential to the activity of the nervous system. In this context, where environment and social relationships seem to be relevant markers for neurodevelopment, advanced neuroimaging techniques and behavioral assessment tools have demonstrated alterations in brain regions and cognitive functions among children developing in low or high socioeconomic status environments. Considering the aspects mentioned, this review aimed to identify the importance of socioeconomic status in children's brain development, seeking to identify what are the impacts of these factors on the morphological and physiological formation of the nervous system, allowing a greater understanding of the importance of environmental factors in neurodevelopmental processes.
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9
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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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10
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Willbrand EH, Ferrer E, Bunge SA, Weiner KS. Development of Human Lateral Prefrontal Sulcal Morphology and Its Relation to Reasoning Performance. J Neurosci 2023; 43:2552-2567. [PMID: 36828638 PMCID: PMC10082454 DOI: 10.1523/jneurosci.1745-22.2023] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 01/25/2023] [Accepted: 02/01/2023] [Indexed: 02/26/2023] Open
Abstract
Previous findings show that the morphology of folds (sulci) of the human cerebral cortex flatten during postnatal development. However, previous studies did not consider the relationship between sulcal morphology and cognitive development in individual participants. Here, we fill this gap in knowledge by leveraging cross-sectional morphologic neuroimaging data in the lateral PFC (LPFC) from individual human participants (6-36 years old, males and females; N = 108; 3672 sulci), as well as longitudinal morphologic and behavioral data from a subset of child and adolescent participants scanned at two time points (6-18 years old; N = 44; 2992 sulci). Manually defining thousands of sulci revealed that LPFC sulcal morphology (depth, surface area, and gray matter thickness) differed between children (6-11 years old)/adolescents (11-18 years old) and young adults (22-36 years old) cross-sectionally, but only cortical thickness showed differences across childhood and adolescence and presented longitudinal changes during childhood and adolescence. Furthermore, a data-driven approach relating morphology and cognition identified that longitudinal changes in cortical thickness of four left-hemisphere LPFC sulci predicted longitudinal changes in reasoning performance, a higher-level cognitive ability that relies on LPFC. Contrary to previous findings, these results suggest that sulci may flatten either after this time frame or over a longer longitudinal period of time than previously presented. Crucially, these results also suggest that longitudinal changes in the cortex within specific LPFC sulci are behaviorally meaningful, providing targeted structures, and areas of the cortex, for future neuroimaging studies examining the development of cognitive abilities.SIGNIFICANCE STATEMENT Recent work has shown that individual differences in neuroanatomical structures (indentations, or sulci) within the lateral PFC are behaviorally meaningful during childhood and adolescence. Here, we describe how specific lateral PFC sulci develop at the level of individual participants for the first time: from both cross-sectional and longitudinal perspectives. Further, we show, also for the first time, that the longitudinal morphologic changes in these structures are behaviorally relevant. These findings lay the foundation for a future avenue to precisely study the development of the cortex and highlight the importance of studying the development of sulci in other cortical expanses and charting how these changes relate to the cognitive abilities those areas support at the level of individual participants.
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Affiliation(s)
- Ethan H Willbrand
- Department of Psychology
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Emilio Ferrer
- Department of Psychology
- Center for Mind and Brain, University of California-Davis, Davis, California 95616
| | - Silvia A Bunge
- Department of Psychology
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Kevin S Weiner
- Department of Psychology
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
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11
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Sydnor VJ, Larsen B, Seidlitz J, Adebimpe A, Alexander-Bloch AF, Bassett DS, Bertolero MA, Cieslak M, Covitz S, Fan Y, Gur RE, Gur RC, Mackey AP, Moore TM, Roalf DR, Shinohara RT, Satterthwaite TD. Intrinsic activity development unfolds along a sensorimotor-association cortical axis in youth. Nat Neurosci 2023; 26:638-649. [PMID: 36973514 PMCID: PMC10406167 DOI: 10.1038/s41593-023-01282-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Animal studies of neurodevelopment have shown that recordings of intrinsic cortical activity evolve from synchronized and high amplitude to sparse and low amplitude as plasticity declines and the cortex matures. Leveraging resting-state functional MRI (fMRI) data from 1,033 youths (ages 8-23 years), we find that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental change. Declines in the amplitude of intrinsic fMRI activity were initiated heterochronously across regions and were coupled to the maturation of intracortical myelin, a developmental plasticity regulator. Spatiotemporal variability in regional developmental trajectories was organized along a hierarchical, sensorimotor-association cortical axis from ages 8 to 18. The sensorimotor-association axis furthermore captured variation in associations between youths' neighborhood environments and intrinsic fMRI activity; associations suggest that the effects of environmental disadvantage on the maturing brain diverge most across this axis during midadolescence. These results uncover a hierarchical neurodevelopmental axis and offer insight into the progression of cortical plasticity in humans.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Azeez Adebimpe
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Covitz
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Kilpatrick L, Zhang K, Dong T, Gee G, Beltran-Sanchez H, Wang M, Labus J, Naliboff B, Mayer E, Gupta A. Mediating role of obesity on the association between disadvantaged neighborhoods and intracortical myelination. RESEARCH SQUARE 2023:rs.3.rs-2592087. [PMID: 36993600 PMCID: PMC10055549 DOI: 10.21203/rs.3.rs-2592087/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We investigated the relationship between neighborhood disadvantage (area deprivation index [ADI]) and intracortical myelination (T1-weighted/T2-weighted ratio at deep to superficial cortical levels), and the potential mediating role of the body mass index (BMI) and perceived stress in 92 adults. Worse ADI was correlated with increased BMI and perceived stress (p's<.05). Non-rotated partial least squares analysis revealed associations between worse ADI and decreased myelination in middle/deep cortex in supramarginal, temporal, and primary motor regions and increased myelination in superficial cortex in medial prefrontal and cingulate regions (p<.001); thus, neighborhood disadvantage may influence the flexibility of information processing involved in reward, emotion regulation, and cognition. Structural equation modelling revealed increased BMI as partially mediating the relationship between worse ADI and observed myelination increases (p=.02). Further, trans-fatty acid intake was correlated with observed myelination increases (p=.03), suggesting the importance of dietary quality. These data further suggest ramifications of neighborhood disadvantage on brain health.
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Affiliation(s)
| | | | - Tien Dong
- University of California Los Angeles
| | | | | | - May Wang
- University of California Los Angeles
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