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Marcelle ET, Yang H, Cohen JW, Ramphal B, Pagliaccio D, Rauh V, Peterson BS, Perera F, Andrews H, Rundle AG, Herbstman J, Margolis AE. The role of the hippocampus in working memory and word reading: Novel neural correlates of reading among youth living in the context of economic disadvantage. Dev Cogn Neurosci 2025; 71:101491. [PMID: 39818176 PMCID: PMC11783422 DOI: 10.1016/j.dcn.2024.101491] [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: 08/14/2024] [Revised: 11/01/2024] [Accepted: 12/09/2024] [Indexed: 01/18/2025] Open
Abstract
A left-lateralized cortical reading circuit underlies successful reading and fails to engage in individuals with reading problems. Studies identifying this circuit included youth from economically advantaged backgrounds and focused on cortical, not subcortical, structures. However, among youth with low scores on reading tests who are living in the context of economic disadvantage, this brain network is actively engaged during reading, despite persistent reading problems. This finding suggests that other brain circuits may underlie reading in these youth. A hippocampal circuit is one likely candidate, as it has recently been shown to support domain-general processes like working memory (WM) that are also associated with reading. Given age-related increases in hippocampal volume, WM, and reading, and known associations between WM and reading, we hypothesized that hippocampal volume would be associated with reading via WM processes. Using a cross-sectional developmental design, we explored this in middle childhood (average age at MRI scan ∼10; N = 50) and adolescence (average age at MRI scan ∼17; N = 175). Results suggest that the hippocampus is a critical contributor to word reading in adolescents living in economically disadvantaged contexts, and that this operates through working memory processes. Such findings point to new targets for reading intervention in adolescents.
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Affiliation(s)
- E T Marcelle
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - H Yang
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - J W Cohen
- Child Mind Institute, New York, NY, USA
| | - B Ramphal
- Harvard TH Chan School of Public Health, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - D Pagliaccio
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - V Rauh
- Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - B S Peterson
- Department of Psychiatry at the Keck School of Medicine, University of Southern California, and Children's Hospital of Los Angeles, Los Angeles, CA, USA
| | - F Perera
- Columbia Center for Children's Environmental Health, Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - H Andrews
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - A G Rundle
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - J Herbstman
- Columbia Center for Children's Environmental Health, Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - A E Margolis
- Child Mind Institute, New York, NY, USA; Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, USA.
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Abo Hamza E, Tindle R, Pawlak S, Bedewy D, Moustafa AA. The impact of poverty and socioeconomic status on brain, behaviour, and development: a unified framework. Rev Neurosci 2024; 35:597-617. [PMID: 38607658 DOI: 10.1515/revneuro-2023-0163] [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: 12/31/2023] [Accepted: 03/17/2024] [Indexed: 04/13/2024]
Abstract
In this article, we, for the first time, provide a comprehensive overview and unified framework of the impact of poverty and low socioeconomic status (SES) on the brain and behaviour. While there are many studies on the impact of low SES on the brain (including cortex, hippocampus, amygdala, and even neurotransmitters) and behaviours (including educational attainment, language development, development of psychopathological disorders), prior studies did not integrate behavioural, educational, and neural findings in one framework. Here, we argue that the impact of poverty and low SES on the brain and behaviour are interrelated. Specifically, based on prior studies, due to a lack of resources, poverty and low SES are associated with poor nutrition, high levels of stress in caregivers and their children, and exposure to socio-environmental hazards. These psychological and physical injuries impact the normal development of several brain areas and neurotransmitters. Impaired functioning of the amygdala can lead to the development of psychopathological disorders, while impaired hippocampus and cortex functions are associated with a delay in learning and language development as well as poor academic performance. This in turn perpetuates poverty in children, leading to a vicious cycle of poverty and psychological/physical impairments. In addition to providing economic aid to economically disadvantaged families, interventions should aim to tackle neural abnormalities caused by poverty and low SES in early childhood. Importantly, acknowledging brain abnormalities due to poverty in early childhood can help increase economic equity. In the current study, we provide a comprehensive list of future studies to help understand the impact of poverty on the brain.
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Affiliation(s)
- Eid Abo Hamza
- College of Education, Humanities & Social Sciences, 289293 Al Ain University , 64141, Al Jimi, UAE
- Faculty of Education, Tanta University, Al-Geish St., 122011, Tanta, Egypt
| | - Richard Tindle
- JMS Allied Services, 1109 Coffs Harbour , NSW, 2452, Australia
| | - Simon Pawlak
- Department of Psychological Sciences, Swinburne University of Technology, John Street, Hawthorn, VIC 3122, Australia
| | - Dalia Bedewy
- Department of Psychology, College of Humanities and Sciences, 59104 Ajman University , University Street, Al jerf 1, Ajman, UAE
- Department of Psychology, Faculty of Education, Tanta University, Al-Geish St., 122011, Tanta, Egypt
- 59104 Humanities and Social Sciences Research Center (HSSRC), Ajman University , University Street, Al jerf 1, Ajman, UAE
| | - Ahmed A Moustafa
- Department of Human Anatomy and Physiology, The Faculty of Health Sciences, University of Johannesburg, Cnr Kingsway & University Roads, Auckland Park, Johannesburg, 2092, South Africa
- School of Psychology, Faculty of Society and Design, 448704 Bond University , 14 University Dr, Robina QLD 4226, Gold Coast, QLD, Australia
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Li G, Cao Y, Yang C, Li X, Yang Y, Yang L, Hao D, Li CSR. Sex differences in dorsolateral prefrontal cortical and superior colliculus activities support the impact of alcohol use severity and sleep deficiency on two-back memory. Quant Imaging Med Surg 2024; 14:4972-4986. [PMID: 39022273 PMCID: PMC11250293 DOI: 10.21037/qims-24-156] [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: 01/25/2024] [Accepted: 05/20/2024] [Indexed: 07/20/2024]
Abstract
Background Working memory refers to a process of temporary storage and manipulation of information to support planning, decision-making, and action. Frequently comorbid alcohol misuse and sleep deficiency have both been associated with working memory deficits. However, how alcohol misuse and sleep deficiency interact to impact working memory remains unclear. In this study, we aim to investigate the neural processes inter-relating alcohol misuse, sleep deficiency and working memory. Methods We curated the Human Connectome Project (HCP) dataset and investigated the neural correlation of working memory in link with alcohol use severity and sleep deficiency in 991 young adults (521 women). The two were indexed by the first principal component (PC1) of principal component analysis of all drinking metrics and Pittsburgh Sleep Quality Index (PSQI) score, respectively. We processed the imaging data with published routines and evaluated the results with a corrected threshold. We used path model to characterize the inter-relationship between the clinical, behavioral, and neural measures, and explored sex differences in the findings. Results In whole-brain regression, we identified β estimates of dorsolateral prefrontal cortex response (DLPFC β) to 2- vs. 0-back in correlation with PC1. The DLPFC showed higher activation in positive correlation with PC1 across men and women (r=0.16, P<0.001). Path analyses showed the model PC1 → DLPFC β → differences in reaction time (2- minus 0-back; RT2-0) of correct trials → differences in critical success index (2- minus 0-back; CSI2-0) with the best fit. In women alone, in addition to the DLPFC, a cluster in the superior colliculus (SC) showed a significant negative correlation with the PSQI score (r=-0.23, P<0.001), and the path model showed the inter-relationship of PC1, PSQI score, DLPFC and SC β's, and CSI2-0 in women. Conclusions Alcohol misuse may involve higher DLPFC activation in functional compensation, whereas, in women only, sleep deficiency affects 2-back memory by depressing SC activity. In women only, path model suggests inter-related impact of drinking severity and sleep deficiency on 2-back memory. These findings suggest potential sex differences in the impact of drinking and sleep problems on working memory that need to be further investigated.
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Affiliation(s)
- Guangfei Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Yingjie Cao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Chunlan Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Xuwen Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Yimin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Lin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Dongmei Hao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
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McCall DM, Homayouni R, Yu Q, Raz S, Ofen N. Meta-Analysis of Hippocampal Volume and Episodic Memory in Preterm and Term Born Individuals. Neuropsychol Rev 2024; 34:478-495. [PMID: 37060422 DOI: 10.1007/s11065-023-09583-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/22/2022] [Indexed: 04/16/2023]
Abstract
Preterm birth (< 37 weeks gestation) has been associated with memory deficits, which has prompted investigation of possible alterations in hippocampal volume in this population. However, existing literature reports varying effects of premature birth on hippocampal volume. Specifically, it is unclear whether smaller hippocampal volume in preterm-born individuals is merely reflective of smaller total brain volume. Further, it is not clear if hippocampal volume is associated with episodic memory functioning in preterm-born individuals. Meta-analysis was used to investigate the effects of premature birth on hippocampal volume and episodic memory from early development to young adulthood (birth to 26). PubMed, PsychINFO, and Web of Science were searched for English peer-reviewed articles that included hippocampal volume of preterm and term-born individuals. Thirty articles met the inclusion criteria. Separate meta-analyses were used to evaluate standardized mean differences between preterm and term-born individuals in uncorrected and corrected hippocampal volume, as well as verbal and visual episodic memory. Both uncorrected and corrected hippocampal volume were smaller in preterm-born compared to term-born individuals. Although preterm-born individuals had lower episodic memory performance than term-born individuals, the limited number of studies only permitted a qualitative review of the association between episodic memory performance and hippocampal volume. Tested moderators included mean age, pre/post-surfactant era, birth weight, gestational age, demarcation method, magnet strength, and slice thickness. With this meta-analysis, we provide novel evidence of the effects of premature birth on hippocampal volume.
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Affiliation(s)
- Dana M McCall
- Institute of Gerontology, Wayne State University, Detroit, MI, USA.
- Department of Neuropsychology, Gundersen Health System, La Crosse, WI, USA.
| | - Roya Homayouni
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
- Department of Psychology, Wayne State University, Detroit, MI, USA
| | - Qijing Yu
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Sarah Raz
- Department of Psychology, Wayne State University, Detroit, MI, USA
- Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI, USA
| | - Noa Ofen
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
- Department of Psychology, Wayne State University, Detroit, MI, USA
- Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI, USA
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Lin Z, Si Y, Kang J. LATENT SUBGROUP IDENTIFICATION IN IMAGE-ON-SCALAR REGRESSION. Ann Appl Stat 2024; 18:468-486. [PMID: 38846637 PMCID: PMC11156244 DOI: 10.1214/23-aoas1797] [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] [Indexed: 06/09/2024]
Abstract
Image-on-scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interventions to increase the number of youths who benefit. It is of great interest to identify subgroups of individuals from the population such that: (1) within each subgroup the brain activities have homogeneous associations with the clinical measures; (2) across subgroups the associations are heterogeneous, and (3) the group allocation depends on individual characteristics. Existing image-on-scalar regression methods and clustering methods cannot directly achieve this goal. We propose a latent subgroup image-on-scalar regression model (LASIR) to analyze large-scale, multisite neuroimaging data with diverse sociode-mographics. LASIR introduces the latent subgroup for each individual and group-specific, spatially varying effects, with an efficient stochastic expectation maximization algorithm for inferences. We demonstrate that LASIR outperforms existing alternatives for subgroup identification of brain activation patterns with functional magnetic resonance imaging data via comprehensive simulations and applications to the ABCD study. We have released our reproducible codes for public use with the software package available on Github.
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Affiliation(s)
- Zikai Lin
- Department of Biostatistics, University of Michigan
| | - Yajuan Si
- Survey Research Center, Institute for Social Research, University of Michigan
| | - Jian Kang
- Department of Biostatistics, University of Michigan
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Menken MS, Isaiah A, Liang H, Rivera PR, Cloak CC, Reeves G, Lever NA, Chang L. Peer victimization (bullying) on mental health, behavioral problems, cognition, and academic performance in preadolescent children in the ABCD Study. Front Psychol 2022; 13:925727. [PMID: 36225678 PMCID: PMC9549775 DOI: 10.3389/fpsyg.2022.925727] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/26/2022] [Indexed: 02/01/2023] Open
Abstract
Objective Peer victimization is a substantial early life stressor linked to psychiatric symptoms and poor academic performance. However, the sex-specific cognitive or behavioral outcomes of bullying have not been well-described in preadolescent children. Methods Using the baseline dataset of the Adolescent Brain Cognitive Development (ABCD) Study 2.0.1 data repository (N = 11,875), we evaluated associations between parent-reported bullying victimization, suicidality (suicidal ideation, intent, and/or behavior), and non-suicidal self-injury (NSSI), as well as internalizing and externalizing behavioral problems, cognition, and academic performance. Results Of the 11,015 9-10-year-old children included in the analyses (5,263 girls), 15.3% experienced bullying victimization, as reported by the primary caregiver. Of these, boys were more likely to be bullied than girls (odds ratio [OR], 1.2 [95% CI, 1.1-1.3]; p = 0.004). Children who were bullied were more likely to display NSSI or passive suicidality (OR, 2.4 [95% CI, 2.0-2.9]; p < 0.001) and active suicidality (OR, 3.4 [95% CI, 2.7-4.2]; p < 0.001). Bullied children also had lower cognitive scores, greater behavioral problems, and poorer grades (p < 0.001). Across all participants, boys had poorer grades and greater behavioral problems than girls; however, bullied boys had greater behavioral problems than girls in several areas (p < 0.001). Compared to their non-bullied peers, bullied children with greater non-suicidal self-injury or suicidality also had greater behavioral problems and poorer grades (p < 0.001). Conclusion These findings highlight the sex-specific effects of bullying, and the negative associations of bullying victimization with cognitive performance, behavioral problems, and academic performance. Future longitudinal studies will identify the natural history and neural correlates of these deficits during adolescence.
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Affiliation(s)
- Miriam S. Menken
- Chang Laboratory, Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Amal Isaiah
- Department of Otorhinolaryngology—Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, United States
- Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Huajun Liang
- Chang Laboratory, Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Pedro Rodriguez Rivera
- Chang Laboratory, Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Christine C. Cloak
- Chang Laboratory, Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Gloria Reeves
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Nancy A. Lever
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Linda Chang
- Chang Laboratory, Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Kim K, Joo YY, Ahn G, Wang HH, Moon SY, Kim H, Ahn WY, Cha J. The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children. Hum Brain Mapp 2022; 43:3857-3872. [PMID: 35471639 PMCID: PMC9294341 DOI: 10.1002/hbm.25888] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/28/2022] [Accepted: 04/05/2022] [Indexed: 11/06/2022] Open
Abstract
Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9-10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC-AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (pfdr < .001, η p 2 $$ {\eta}_p^2 $$ = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (pfdr < .001, η p 2 $$ {\eta}_p^2 $$ < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006-.009; p = .002-.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene-brain-cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.
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Affiliation(s)
- Kakyeong Kim
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | | | - Gun Ahn
- Interdisciplinary Program of Bioengineering, College of Engineering, Seoul National University, Seoul, South Korea
| | - Hee-Hwan Wang
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Seo-Yoon Moon
- College of Liberal Studies, Seoul National University, Seoul, South Korea
| | - Hyeonjin Kim
- Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea
| | - Woo-Young Ahn
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea.,Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea.,AI Institute, Seoul National University, Seoul, South Korea
| | - Jiook Cha
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea.,Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea.,AI Institute, Seoul National University, Seoul, South Korea
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