Pub Date : 2024-10-16DOI: 10.1016/j.dcn.2024.101462
Sandra Thijssen , Yllza Xerxa , Linn B. Norbom , Maaike Cima , Henning Tiemeier , Christian K. Tamnes , Ryan L. Muetzel
Early threat-associated cortical thinning may be interpreted as accelerated cortical development. However, non-adaptive processes may show similar macrostructural changes. Examining cortical thickness (CT) together with grey/white-matter contrast (GWC), a proxy for intracortical myelination, may enhance the interpretation of CT findings. In this prospective study, we examined associations between early life family-related threat (harsh parenting, family conflict, and neighborhood safety) and CT and GWC development from late childhood to middle adolescence. MRI was acquired from 4200 children (2069 boys) from the Generation R study at ages 8, 10 and 14 years (in total 6114 scans), of whom 1697 children had >1 scans. Linear mixed effect models were used to examine family factor-by-age interactions on amygdala volume, caudal and rostral anterior cingulate (ACC) and medial orbitofrontal cortex (mOFC) CT and GWC. A neighborhood safety-by-age-interaction was found for rostral ACC GWC, suggesting less developmental change in children from unsafe neighborhoods. Moreover, after more stringent correction for motion, family conflict was associated with greater developmental change in CT but less developmental change in GWC. Results suggest that early threat may blunt ACC GWC development. Our results, therefore, do not provide evidence for accelerated threat-associated structural development of the amygdala-mPFC circuit between ages 8–14 years.
{"title":"Early childhood family threat and longitudinal amygdala-mPFC circuit development: Examining cortical thickness and gray matter-white matter contrast","authors":"Sandra Thijssen , Yllza Xerxa , Linn B. Norbom , Maaike Cima , Henning Tiemeier , Christian K. Tamnes , Ryan L. Muetzel","doi":"10.1016/j.dcn.2024.101462","DOIUrl":"10.1016/j.dcn.2024.101462","url":null,"abstract":"<div><div>Early threat-associated cortical thinning may be interpreted as accelerated cortical development. However, non-adaptive processes may show similar macrostructural changes. Examining cortical thickness (CT) together with grey/white-matter contrast (GWC), a proxy for intracortical myelination, may enhance the interpretation of CT findings. In this prospective study, we examined associations between early life family-related threat (harsh parenting, family conflict, and neighborhood safety) and CT and GWC development from late childhood to middle adolescence. MRI was acquired from 4200 children (2069 boys) from the Generation R study at ages 8, 10 and 14 years (in total 6114 scans), of whom 1697 children had >1 scans. Linear mixed effect models were used to examine family factor-by-age interactions on amygdala volume, caudal and rostral anterior cingulate (ACC) and medial orbitofrontal cortex (mOFC) CT and GWC. A neighborhood safety-by-age-interaction was found for rostral ACC GWC, suggesting less developmental change in children from unsafe neighborhoods. Moreover, after more stringent correction for motion, family conflict was associated with greater developmental change in CT but less developmental change in GWC. Results suggest that early threat may blunt ACC GWC development. Our results, therefore, do not provide evidence for accelerated threat-associated structural development of the amygdala-mPFC circuit between ages 8–14 years.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101462"},"PeriodicalIF":4.6,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.dcn.2024.101464
Brendan D. Adkinson , Matthew Rosenblatt , Javid Dadashkarimi , Link Tejavibulya , Rongtao Jiang , Stephanie Noble , Dustin Scheinost
Predictive modeling potentially increases the reproducibility and generalizability of neuroimaging brain-phenotype associations. Yet, the evaluation of a model in another dataset is underutilized. Among studies that undertake external validation, there is a notable lack of attention to generalization across dataset-specific idiosyncrasies (i.e., dataset shifts). Research settings, by design, remove the between-site variations that real-world and, eventually, clinical applications demand. Here, we rigorously test the ability of a range of predictive models to generalize across three diverse, unharmonized developmental samples: the Philadelphia Neurodevelopmental Cohort (n=1291), the Healthy Brain Network (n=1110), and the Human Connectome Project in Development (n=428). These datasets have high inter-dataset heterogeneity, encompassing substantial variations in age distribution, sex, racial and ethnic minority representation, recruitment geography, clinical symptom burdens, fMRI tasks, sequences, and behavioral measures. Through advanced methodological approaches, we demonstrate that reproducible and generalizable brain-behavior associations can be realized across diverse dataset features. Results indicate the potential of functional connectome-based predictive models to be robust despite substantial inter-dataset variability. Notably, for the HCPD and HBN datasets, the best predictions were not from training and testing in the same dataset (i.e., cross-validation) but across datasets. This result suggests that training on diverse data may improve prediction in specific cases. Overall, this work provides a critical foundation for future work evaluating the generalizability of brain-phenotype associations in real-world scenarios and clinical settings.
{"title":"Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations","authors":"Brendan D. Adkinson , Matthew Rosenblatt , Javid Dadashkarimi , Link Tejavibulya , Rongtao Jiang , Stephanie Noble , Dustin Scheinost","doi":"10.1016/j.dcn.2024.101464","DOIUrl":"10.1016/j.dcn.2024.101464","url":null,"abstract":"<div><div>Predictive modeling potentially increases the reproducibility and generalizability of neuroimaging brain-phenotype associations. Yet, the evaluation of a model in another dataset is underutilized. Among studies that undertake external validation, there is a notable lack of attention to generalization across dataset-specific idiosyncrasies (i.e., dataset shifts). Research settings, by design, remove the between-site variations that real-world and, eventually, clinical applications demand. Here, we rigorously test the ability of a range of predictive models to generalize across three diverse, unharmonized developmental samples: the Philadelphia Neurodevelopmental Cohort (n=1291), the Healthy Brain Network (n=1110), and the Human Connectome Project in Development (n=428). These datasets have high inter-dataset heterogeneity, encompassing substantial variations in age distribution, sex, racial and ethnic minority representation, recruitment geography, clinical symptom burdens, fMRI tasks, sequences, and behavioral measures. Through advanced methodological approaches, we demonstrate that reproducible and generalizable brain-behavior associations can be realized across diverse dataset features. Results indicate the potential of functional connectome-based predictive models to be robust despite substantial inter-dataset variability. Notably, for the HCPD and HBN datasets, the best predictions were not from training and testing in the same dataset (i.e., cross-validation) but across datasets. This result suggests that training on diverse data may improve prediction in specific cases. Overall, this work provides a critical foundation for future work evaluating the generalizability of brain-phenotype associations in real-world scenarios and clinical settings.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101464"},"PeriodicalIF":4.6,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142511332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-12DOI: 10.1016/j.dcn.2024.101459
Serena K. Mon , Brittany L. Manning , Lauren S. Wakschlag , Elizabeth S. Norton
Trial-by-trial neural variability, a measure of neural response stability, has been examined in relation to behavioral indicators using summary measures, but these methods do not characterize meaningful processes underlying variability. Mixed-effects location scale models (MELSMs) overcome these limitations by accounting for predictors and covariates of variability but have been rarely used in developmental studies. Here, we applied MELSMs to the ERP auditory mismatch negativity (MMN), a neural measure often related to language and psychopathology. 84 toddlers and 76 mothers completed a speech-syllable MMN paradigm. We extracted early and late MMN mean amplitudes from trial-level waveforms. We first characterized our sample’s psychometric properties using MELSMs and found a wide range of subject-level internal consistency. Next, we examined the relation between toddler MMNs with theoretically relevant child behavioral and maternal variables. MELSMs offered better model fit than analyses that assumed constant variability. We found significant individual differences in trial-by-trial variability but no significant associations between toddler variability and their language, irritability, or mother variability indices. Overall, we illustrate how MELSMs can characterize psychometric properties and answer questions about individual differences in variability. We provide recommendations and resources as well as example code for analyzing trial-by-trial neural variability in future studies.
{"title":"Leveraging mixed-effects location scale models to assess the ERP mismatch negativity’s psychometric properties and trial-by-trial neural variability in toddler-mother dyads","authors":"Serena K. Mon , Brittany L. Manning , Lauren S. Wakschlag , Elizabeth S. Norton","doi":"10.1016/j.dcn.2024.101459","DOIUrl":"10.1016/j.dcn.2024.101459","url":null,"abstract":"<div><div>Trial-by-trial neural variability, a measure of neural response stability, has been examined in relation to behavioral indicators using summary measures, but these methods do not characterize meaningful processes underlying variability. Mixed-effects location scale models (MELSMs) overcome these limitations by accounting for predictors and covariates of variability but have been rarely used in developmental studies. Here, we applied MELSMs to the ERP auditory mismatch negativity (MMN), a neural measure often related to language and psychopathology. 84 toddlers and 76 mothers completed a speech-syllable MMN paradigm. We extracted early and late MMN mean amplitudes from trial-level waveforms. We first characterized our sample’s psychometric properties using MELSMs and found a wide range of subject-level internal consistency. Next, we examined the relation between toddler MMNs with theoretically relevant child behavioral and maternal variables. MELSMs offered better model fit than analyses that assumed constant variability. We found significant individual differences in trial-by-trial variability but no significant associations between toddler variability and their language, irritability, or mother variability indices. Overall, we illustrate how MELSMs can characterize psychometric properties and answer questions about individual differences in variability. We provide recommendations and resources as well as example code for analyzing trial-by-trial neural variability in future studies.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101459"},"PeriodicalIF":4.6,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-28DOI: 10.1016/j.dcn.2024.101461
Julie A. Kable , Alexandra S. Potter , Natacha Akshoomoff , Patricia M. Blasco , Stefanie C. Bodison , Lucia Ciciolla , Sherry DeGray , Zoe Hulce , Emily S. Kuschner , Britley Learnard , Monica Luciana , Alexandra Perez , Miriam A. Novack , Tracy Riggins , So Yeon Shin , Sidney Smith , Jennifer Vannest , Eric.H. Zimak , the HBCD Neurocognitive and Language (NCL) Workgroup
The HEALthy Brain and Child Development (HBCD) study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The study plans enrolling over 7000 families across 27 sites. This manuscript presents the measures from the Neurocognition and Language Workgroup. Constructs were selected for their importance in normative development, evidence for altered trajectories associated with environmental influences, and predictive validity for child outcomes. Evaluation of measures considered psychometric properties, brevity, and developmental and cultural appropriateness. Both performance measures and caregiver report were used wherever possible. A balance of norm-referenced global measures of development (e.g., Bayley Scales of Infant Development-4) and more specific laboratory measures (e.g., deferred imitation) are included in the HBCD study battery. Domains of assessment include sensory processing, visual-spatial reasoning, expressive and receptive language, executive function, memory, numeracy, adaptive behavior, and neuromotor. Strategies for staff training and quality control procedures, as well as anticipated measures to be added as the cohort ages, are reviewed. The HBCD study presents a unique opportunity to examine early brain and neurodevelopment in young children through a lens that accounts for prenatal exposures, health and socio-economic disparities.
{"title":"Measurement of emerging neurocognitive and language skills in the HEALthy Brain and Child Development (HBCD) study","authors":"Julie A. Kable , Alexandra S. Potter , Natacha Akshoomoff , Patricia M. Blasco , Stefanie C. Bodison , Lucia Ciciolla , Sherry DeGray , Zoe Hulce , Emily S. Kuschner , Britley Learnard , Monica Luciana , Alexandra Perez , Miriam A. Novack , Tracy Riggins , So Yeon Shin , Sidney Smith , Jennifer Vannest , Eric.H. Zimak , the HBCD Neurocognitive and Language (NCL) Workgroup","doi":"10.1016/j.dcn.2024.101461","DOIUrl":"10.1016/j.dcn.2024.101461","url":null,"abstract":"<div><div>The HEALthy Brain and Child Development (HBCD) study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The study plans enrolling over 7000 families across 27 sites. This manuscript presents the measures from the Neurocognition and Language Workgroup. Constructs were selected for their importance in normative development, evidence for altered trajectories associated with environmental influences, and predictive validity for child outcomes. Evaluation of measures considered psychometric properties, brevity, and developmental and cultural appropriateness. Both performance measures and caregiver report were used wherever possible. A balance of norm-referenced global measures of development (e.g., Bayley Scales of Infant Development-4) and more specific laboratory measures (e.g., deferred imitation) are included in the HBCD study battery. Domains of assessment include sensory processing, visual-spatial reasoning, expressive and receptive language, executive function, memory, numeracy, adaptive behavior, and neuromotor. Strategies for staff training and quality control procedures, as well as anticipated measures to be added as the cohort ages, are reviewed. The HBCD study presents a unique opportunity to examine early brain and neurodevelopment in young children through a lens that accounts for prenatal exposures, health and socio-economic disparities.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101461"},"PeriodicalIF":4.6,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-28DOI: 10.1016/j.dcn.2024.101458
Wenyi Xu , Alexa D. Monachino , Sarah A. McCormick , Emma T. Margolis , Ana Sobrino , Cara Bosco , Cassandra J. Franke , Lauren Davel , Michal R. Zieff , Kirsten A. Donald , Laurel J. Gabard-Durnam , Santiago Morales
EEG studies play a crucial role in enhancing our understanding of brain development across the lifespan. The increasing clinical and policy implications of EEG research underscore the importance of utilizing reliable EEG measures and increasing the reproducibility of EEG studies. However, important data characteristics like reliability, effect sizes, and data quality metrics are often underreported in pediatric EEG studies. This gap in reporting could stem from the lack of accessible computational tools for quantifying these metrics for EEG data. To help address the lack of reporting, we developed a toolbox that facilitates the estimation of internal consistency reliability, effect size, and standardized measurement error with user-friendly software that facilitates both computing and interpreting these measures. In addition, our tool provides subsampled reliability and effect size in increasing numbers of trials. These estimates offer insights into the number of trials needed for detecting significant effects and reliable measures, informing the minimum number of trial thresholds for the inclusion of participants in individual difference analyses and the optimal trial number for future study designs. Importantly, our toolbox is integrated into commonly used preprocessing pipelines to increase the estimation and reporting of data quality metrics in developmental neuroscience.
{"title":"Advancing the reporting of pediatric EEG data: Tools for estimating reliability, effect size, and data quality metrics","authors":"Wenyi Xu , Alexa D. Monachino , Sarah A. McCormick , Emma T. Margolis , Ana Sobrino , Cara Bosco , Cassandra J. Franke , Lauren Davel , Michal R. Zieff , Kirsten A. Donald , Laurel J. Gabard-Durnam , Santiago Morales","doi":"10.1016/j.dcn.2024.101458","DOIUrl":"10.1016/j.dcn.2024.101458","url":null,"abstract":"<div><div>EEG studies play a crucial role in enhancing our understanding of brain development across the lifespan. The increasing clinical and policy implications of EEG research underscore the importance of utilizing reliable EEG measures and increasing the reproducibility of EEG studies. However, important data characteristics like reliability, effect sizes, and data quality metrics are often underreported in pediatric EEG studies. This gap in reporting could stem from the lack of accessible computational tools for quantifying these metrics for EEG data. To help address the lack of reporting, we developed a toolbox that facilitates the estimation of internal consistency reliability, effect size, and standardized measurement error with user-friendly software that facilitates both computing and interpreting these measures. In addition, our tool provides subsampled reliability and effect size in increasing numbers of trials. These estimates offer insights into the number of trials needed for detecting significant effects and reliable measures, informing the minimum number of trial thresholds for the inclusion of participants in individual difference analyses and the optimal trial number for future study designs. Importantly, our toolbox is integrated into commonly used preprocessing pipelines to increase the estimation and reporting of data quality metrics in developmental neuroscience.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101458"},"PeriodicalIF":4.6,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1016/j.dcn.2024.101454
Gillian Debra, Nathalie Michels, Matteo Giletta
Cognitive control processes likely influence the extent to which adolescents can successfully regulate their emotions. This study examined whether individual differences in affective inhibition and heart rate variability (HRV), as a peripheral index of cognitive control, moderated the association between momentary emotion regulation and negative affect (NA). Ecological Momentary Assessments (EMA) over 14 days were obtained in 235 adolescents (Mage = 13.48 years; 106 females). At each assessment, participants reported their current NA and the extent to which they used cognitive reappraisal and rumination. Moreover, at three time points (approximately 1 year, 6 months, and just before the EMA), affective inhibition was assessed using an affective go/no-go task and HRV was recorded at rest. Results indicate that adolescents with lower affective inhibition reported lower average levels of daily rumination. However, affective inhibition did not moderate the association between either daily cognitive reappraisal or rumination and momentary NA. Consistent with hypotheses, the association between momentary rumination and NA was weaker in adolescents showing higher levels of resting HRV. Overall, findings may underscore the importance of interventions targeting HRV as a malleable factor for enhancing adolescents’ affective well-being.
{"title":"Cognitive control processes and emotion regulation in adolescence: Examining the impact of affective inhibition and heart-rate-variability on emotion regulation dynamics in daily life","authors":"Gillian Debra, Nathalie Michels, Matteo Giletta","doi":"10.1016/j.dcn.2024.101454","DOIUrl":"10.1016/j.dcn.2024.101454","url":null,"abstract":"<div><div>Cognitive control processes likely influence the extent to which adolescents can successfully regulate their emotions. This study examined whether individual differences in affective inhibition and heart rate variability (HRV), as a peripheral index of cognitive control, moderated the association between momentary emotion regulation and negative affect (NA). Ecological Momentary Assessments (EMA) over 14 days were obtained in 235 adolescents (<em>M</em><sub><em>age</em></sub> = 13.48 years; 106 females). At each assessment, participants reported their current NA and the extent to which they used cognitive reappraisal and rumination. Moreover, at three time points (approximately 1 year, 6 months, and just before the EMA), affective inhibition was assessed using an affective go/no-go task and HRV was recorded at rest. Results indicate that adolescents with lower affective inhibition reported lower average levels of daily rumination. However, affective inhibition did not moderate the association between either daily cognitive reappraisal or rumination and momentary NA. Consistent with hypotheses, the association between momentary rumination and NA was weaker in adolescents showing higher levels of resting HRV. Overall, findings may underscore the importance of interventions targeting HRV as a malleable factor for enhancing adolescents’ affective well-being.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101454"},"PeriodicalIF":4.6,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1016/j.dcn.2024.101453
Miguel Ângelo Andrade , Ana Raposo , Alexandre Andrade
Previous research suggests that episodic memory relies on functional neural networks,which are present even in the absence of an explicit task. The regions that integrate.these networks and the developmental changes in intrinsic functional connectivity.remain elusive. In the present study, we outlined an intrinsic episodic memory network.(iEMN) based on a systematic selection of functional connectivity studies, and.inspected network differences in resting-state fMRI between adolescents (13–17 years.old) and adults (23–27 years old) from the publicly available NKI-Rockland Sample.Through a review of brain regions commonly associated with episodic memory.networks, we identified a potential iEMN composed by 14 bilateral ROIs, distributed.across temporal, frontal and parietal lobes. Within this network, we found an increase.in resting-state connectivity from adolescents to adults between the right temporal pole.and two regions in the right lateral prefrontal cortex. We argue that the coordination of.these brain regions, connecting areas of semantic processing and areas of controlled.retrieval, arises as an important feature towards the full maturation of the episodic.memory system. The findings add to evidence suggesting that adolescence is a key.period in memory development and highlights the role of intrinsic functional.connectivity in such development.
{"title":"Exploring the late maturation of an intrinsic episodic memory network: A resting-state fMRI study","authors":"Miguel Ângelo Andrade , Ana Raposo , Alexandre Andrade","doi":"10.1016/j.dcn.2024.101453","DOIUrl":"10.1016/j.dcn.2024.101453","url":null,"abstract":"<div><div>Previous research suggests that episodic memory relies on functional neural networks,which are present even in the absence of an explicit task. The regions that integrate.these networks and the developmental changes in intrinsic functional connectivity.remain elusive. In the present study, we outlined an intrinsic episodic memory network.(iEMN) based on a systematic selection of functional connectivity studies, and.inspected network differences in resting-state fMRI between adolescents (13–17 years.old) and adults (23–27 years old) from the publicly available NKI-Rockland Sample.Through a review of brain regions commonly associated with episodic memory.networks, we identified a potential iEMN composed by 14 bilateral ROIs, distributed.across temporal, frontal and parietal lobes. Within this network, we found an increase.in resting-state connectivity from adolescents to adults between the right temporal pole.and two regions in the right lateral prefrontal cortex. We argue that the coordination of.these brain regions, connecting areas of semantic processing and areas of controlled.retrieval, arises as an important feature towards the full maturation of the episodic.memory system. The findings add to evidence suggesting that adolescence is a key.period in memory development and highlights the role of intrinsic functional.connectivity in such development.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101453"},"PeriodicalIF":4.6,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.dcn.2024.101455
Camille M. Williams , David G. Weissman , Travis T. Mallard , Katie A. McLaughlin , K. Paige Harden
We investigate whether neural, cognitive, and psychopathology phenotypes that are more strongly related to genetic differences are less strongly associated with family- and state-level economic contexts (N = 5374 individuals with 1KG-EUR-like genotypes with 870 twins, from the Adolescent Behavior and Cognitive Development study). We estimated the twin- and SNP-based heritability of each phenotype, as well as its association with an educational attainment polygenic index (EA PGI). We further examined associations with family socioeconomic status (SES) and tested whether SES-related differences were moderated by state cost of living and social safety net programs (Medicaid expansion and cash assistance). SES was broadly associated with cognition, psychopathology, brain volumes, and cortical surface areas, even after controlling for the EA PGI. Brain phenotypes that were more heritable or more strongly associated with the EA PGI were not, overall, less related to SES, nor were SES-related differences in these phenotypes less moderated by macroeconomic context and policy. Informing a long-running theoretical debate, and contra to widespread lay beliefs, results suggest that aspects of child brain development that are more strongly related to genetic differences are not, in general, less associated with socioeconomic contexts and policies.
我们研究了与遗传差异关系更密切的神经、认知和精神病理学表型是否与家庭和国家层面的经济环境关系不大（N = 5374 个具有 1KG-EUR 类基因型的个体，其中有 870 个双胞胎，来自青少年行为和认知发展研究）。我们估算了每种表型的双胞胎遗传率和基于 SNP 的遗传率，以及其与教育程度多基因指数（EA PGI）的关联。我们进一步研究了与家庭社会经济地位（SES）的关联，并检验了与家庭社会经济地位相关的差异是否受到州生活成本和社会安全网计划（医疗补助扩展和现金援助）的调节。即使在控制了 EA PGI 后，社会经济地位仍与认知、精神病理学、脑容量和皮质表面积广泛相关。总体而言，遗传性更强或与 EA PGI 关联性更强的大脑表型与社会经济地位的相关性并不低，这些表型中与社会经济地位相关的差异受宏观经济环境和政策的调节作用也不低。研究结果表明，儿童大脑发育中与遗传差异关系更密切的方面与社会经济背景和政策的关系总体上并不较小，这为长期的理论争论提供了依据，同时也与普遍的非专业观点相悖。
{"title":"Brain structures with stronger genetic associations are not less associated with family- and state-level economic contexts","authors":"Camille M. Williams , David G. Weissman , Travis T. Mallard , Katie A. McLaughlin , K. Paige Harden","doi":"10.1016/j.dcn.2024.101455","DOIUrl":"10.1016/j.dcn.2024.101455","url":null,"abstract":"<div><div>We investigate whether neural, cognitive, and psychopathology phenotypes that are more strongly related to genetic differences are less strongly associated with family- and state-level economic contexts (N = 5374 individuals with 1KG-EUR-like genotypes with 870 twins, from the Adolescent Behavior and Cognitive Development study). We estimated the twin- and SNP-based heritability of each phenotype, as well as its association with an educational attainment polygenic index (EA PGI). We further examined associations with family socioeconomic status (SES) and tested whether SES-related differences were moderated by state cost of living and social safety net programs (Medicaid expansion and cash assistance). SES was broadly associated with cognition, psychopathology, brain volumes, and cortical surface areas, even after controlling for the EA PGI. Brain phenotypes that were more heritable or more strongly associated with the EA PGI were not, overall, less related to SES, nor were SES-related differences in these phenotypes less moderated by macroeconomic context and policy. Informing a long-running theoretical debate, and contra to widespread lay beliefs, results suggest that aspects of child brain development that are more strongly related to genetic differences are not, in general, less associated with socioeconomic contexts and policies.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101455"},"PeriodicalIF":4.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.dcn.2024.101450
Andreas M. Brandmaier , Ulman Lindenberger , Ethan M. McCormick
Based on findings from a simulation study, Parsons and McCormick (2024) argued that growth models with exactly two time points are poorly-suited to model individual differences in linear slopes in developmental studies. Their argument is based on an empirical investigation of the increase in precision to measure individual differences in linear slopes if studies are progressively extended by adding an extra measurement occasion after one unit of time (e.g., year) has passed. They concluded that two-time point models are inadequate to reliably model change at the individual level and that these models should focus on group-level effects. Here, we show that these limitations can be addressed by deconfounding the influence of study duration and the influence of adding an extra measurement occasion on precision to estimate individual differences in linear slopes. We use asymptotic results to gauge and compare precision of linear change models representing different study designs, and show that it is primarily the longer time span that increases precision, not the extra waves. Further, we show how the asymptotic results can be used to also consider irregularly spaced intervals as well as planned and unplanned missing data. In conclusion, we like to stress that true linear change can indeed be captured well with only two time points if careful study design planning is applied before running a study.
{"title":"Optimal two-time point longitudinal models for estimating individual-level change: Asymptotic insights and practical implications","authors":"Andreas M. Brandmaier , Ulman Lindenberger , Ethan M. McCormick","doi":"10.1016/j.dcn.2024.101450","DOIUrl":"10.1016/j.dcn.2024.101450","url":null,"abstract":"<div><div>Based on findings from a simulation study, Parsons and McCormick (2024) argued that growth models with exactly two time points are poorly-suited to model individual differences in linear slopes in developmental studies. Their argument is based on an empirical investigation of the increase in precision to measure individual differences in linear slopes if studies are progressively extended by adding an extra measurement occasion after one unit of time (e.g., year) has passed. They concluded that two-time point models are inadequate to reliably model change at the individual level and that these models should focus on group-level effects. Here, we show that these limitations can be addressed by deconfounding the influence of study duration and the influence of adding an extra measurement occasion on precision to estimate individual differences in linear slopes. We use asymptotic results to gauge and compare precision of linear change models representing different study designs, and show that it is primarily the longer time span that increases precision, not the extra waves. Further, we show how the asymptotic results can be used to also consider irregularly spaced intervals as well as planned and unplanned missing data. In conclusion, we like to stress that true linear change can indeed be captured well with only two time points if careful study design planning is applied before running a study.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101450"},"PeriodicalIF":4.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1016/j.dcn.2024.101443
Lorenza Dall’Aglio , Saúl Urbina Johanson , Travis Mallard , Sander Lamballais , Scott Delaney , Jordan W. Smoller , Ryan L. Muetzel , Henning Tiemeier
Thanks to methodological advances, large-scale data collections, and longitudinal designs, psychiatric neuroimaging is better equipped than ever to identify the neurobiological underpinnings of youth mental health problems. However, the complexity of such endeavors has become increasingly evident, as the field has been confronted by limited clinical relevance, inconsistent results, and small effect sizes. Some of these challenges parallel those historically encountered by psychiatric genetics. In past genetic research, robust findings were historically undermined by oversimplified biological hypotheses, mistaken assumptions about expectable effect sizes, replication problems, confounding by population structure, and shared biological patterns across disorders. Overcoming these challenges has contributed to current successes in the field. Drawing parallels across psychiatric genetics and neuroimaging, we identify key shared challenges as well as pinpoint relevant insights that could be gained in psychiatric neuroimaging from the transition that occurred from the candidate gene to (post) genome-wide “eras” of psychiatric genetics. Finally, we discuss the prominent developmental component of psychiatric neuroimaging and how that might be informed by epidemiological and omics approaches. The evolution of psychiatric genetic research offers valuable insights that may expedite the resolution of key challenges in psychiatric neuroimaging, thus potentially moving our understanding of psychiatric pathophysiology forward.
{"title":"Psychiatric neuroimaging at a crossroads: Insights from psychiatric genetics","authors":"Lorenza Dall’Aglio , Saúl Urbina Johanson , Travis Mallard , Sander Lamballais , Scott Delaney , Jordan W. Smoller , Ryan L. Muetzel , Henning Tiemeier","doi":"10.1016/j.dcn.2024.101443","DOIUrl":"10.1016/j.dcn.2024.101443","url":null,"abstract":"<div><div>Thanks to methodological advances, large-scale data collections, and longitudinal designs, psychiatric neuroimaging is better equipped than ever to identify the neurobiological underpinnings of youth mental health problems. However, the complexity of such endeavors has become increasingly evident, as the field has been confronted by limited clinical relevance, inconsistent results, and small effect sizes. Some of these challenges parallel those historically encountered by psychiatric genetics. In past genetic research, robust findings were historically undermined by oversimplified biological hypotheses, mistaken assumptions about expectable effect sizes, replication problems, confounding by population structure, and shared biological patterns across disorders. Overcoming these challenges has contributed to current successes in the field. Drawing parallels across psychiatric genetics and neuroimaging, we identify key shared challenges as well as pinpoint relevant insights that could be gained in psychiatric neuroimaging from the transition that occurred from the candidate gene to (post) genome-wide “eras” of psychiatric genetics. Finally, we discuss the prominent developmental component of psychiatric neuroimaging and how that might be informed by epidemiological and <em>omics</em> approaches. The evolution of psychiatric genetic research offers valuable insights that may expedite the resolution of key challenges in psychiatric neuroimaging, thus potentially moving our understanding of psychiatric pathophysiology forward.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101443"},"PeriodicalIF":4.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号