Pub Date : 2024-10-29DOI: 10.1016/j.dcn.2024.101468
Julie M. Schneider , Jeahong Kim , Sonali Poudel , Yune S. Lee , Mandy J. Maguire
Children’s socioeconomic status (SES) is related to patterns of intrinsic resting-state brain function that subserve relevant cognitive processes over the course of development. Although infant research has demonstrated the association between children’s environments, cognitive outcomes, and resting-state electroencephalography (rsEEG), it remains unknown how these aspects of their environment, tied to SES, impact neural and cognitive development throughout the school years. To address this gap, we applied a multivariate pattern analysis (MVPA) to rsEEG data to identify which neural frequencies at rest are differentially associated with unique aspects of socioeconomic status (SES; income and maternal education) and cognitive (vocabulary, working memory) outcomes among school-aged children (8–15 years). We find that the alpha frequency is associated with both income and maternal education, while lower gamma and theta fluctuations are tied to dissociable aspects of SES and cognitive outcomes. Specifically, changes in the gamma frequency are predictive of both maternal education and vocabulary outcome, while changes in the theta frequency are related to both income and working memory ability. The current findings extend our understanding of unique pathways by which SES influences cognitive and neural development in school-aged children.
{"title":"Socioeconomic status (SES) and cognitive outcomes are predicted by resting-state EEG in school-aged children","authors":"Julie M. Schneider , Jeahong Kim , Sonali Poudel , Yune S. Lee , Mandy J. Maguire","doi":"10.1016/j.dcn.2024.101468","DOIUrl":"10.1016/j.dcn.2024.101468","url":null,"abstract":"<div><div>Children’s socioeconomic status (SES) is related to patterns of intrinsic resting-state brain function that subserve relevant cognitive processes over the course of development. Although infant research has demonstrated the association between children’s environments, cognitive outcomes, and resting-state electroencephalography (rsEEG), it remains unknown how these aspects of their environment, tied to SES, impact neural and cognitive development throughout the school years. To address this gap, we applied a multivariate pattern analysis (MVPA) to rsEEG data to identify which neural frequencies at rest are differentially associated with unique aspects of socioeconomic status (SES; income and maternal education) and cognitive (vocabulary, working memory) outcomes among school-aged children (8–15 years). We find that the alpha frequency is associated with both income and maternal education, while lower gamma and theta fluctuations are tied to dissociable aspects of SES and cognitive outcomes. Specifically, changes in the gamma frequency are predictive of both maternal education and vocabulary outcome, while changes in the theta frequency are related to both income and working memory ability. The current findings extend our understanding of unique pathways by which SES influences cognitive and neural development in school-aged children.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101468"},"PeriodicalIF":4.6,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587318","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 : 2024-10-29DOI: 10.1016/j.dcn.2024.101469
Emily J. Furtado , M. Catalina Camacho , Jenna H. Chin , Deanna M. Barch
Objective
Early life adversity (ELA) has shown to have negative impacts on mental health. One possible mechanism is through alterations in neural emotion processing. We sought to characterize how multiple indices of ELA were related to naturalistic neural socio-emotional processing.
Method
In 521 5–15-year-old participants from the Healthy Brain Network Biobank, we identified scenes that elicited activation of the Default Mode Network (DMN), Ventral Attention Network (VAN), Cingulo-Opercular Network (CON) and amygdala, all of which are networks shown to be associated with ELA. We used linear regression to examine associations between activation and ELA: negative parenting, social status, financial insecurity, neighborhood disadvantage, negative experiences, and parent psychopathology.
Results
We found DMN, VAN, CON and amygdala activation during sad/emotional, bonding, action, conflict, sad, or fearful scenes. Greater inconsistent discipline was associated with greater VAN activation during sad or emotional scenes.
Conclusion
Findings suggest that the DMN, VAN, CON networks and the amygdala support socio-emotional processing consistent with prior literature. Individuals who experienced inconsistent discipline may have greater sensitivity to parent–child separation signals. Since no other ELA–activation associations were found, it is possible that unpredictability may be more strongly associated with complex neural emotion processing than socio-economic status or negative life events.
目的：早期生活逆境（ELA）已被证明会对心理健康产生负面影响。一种可能的机制是通过改变神经情绪处理。我们试图描述 ELA 的多个指数与自然神经社会情绪处理的关系：在健康脑网络生物库的 521 名 5-15 岁参与者中，我们确定了能引起默认模式网络 (DMN)、腹侧注意网络 (VAN)、鞘膜-眼球网络 (CON) 和杏仁核激活的场景，所有这些网络都被证明与 ELA 相关。我们使用线性回归法研究了激活与幼儿语言学习之间的关联：负面养育、社会地位、经济不安全、邻里关系不利、负面经历和父母的精神病理学：我们发现，在悲伤/情绪、亲情、行动、冲突、悲伤或恐惧场景中，DMN、VAN、CON和杏仁核被激活。结论：研究结果表明，在悲伤或情绪场景中，管教不一致程度越高，VAN激活程度越高：研究结果表明，DMN、VAN、CON网络和杏仁核支持社会情感处理，这与之前的文献一致。经历过不一致管教的个体可能对亲子分离信号更为敏感。由于没有发现其他ELA激活关联，因此与社会经济地位或负面生活事件相比，不可预测性可能与复杂的神经情绪处理有更强的关联。
{"title":"Complex emotion processing and early life adversity in the Healthy Brain Network sample","authors":"Emily J. Furtado , M. Catalina Camacho , Jenna H. Chin , Deanna M. Barch","doi":"10.1016/j.dcn.2024.101469","DOIUrl":"10.1016/j.dcn.2024.101469","url":null,"abstract":"<div><h3>Objective</h3><div>Early life adversity (ELA) has shown to have negative impacts on mental health. One possible mechanism is through alterations in neural emotion processing. We sought to characterize how multiple indices of ELA were related to naturalistic neural socio-emotional processing.</div></div><div><h3>Method</h3><div>In 521 5–15-year-old participants from the Healthy Brain Network Biobank, we identified scenes that elicited activation of the Default Mode Network (DMN), Ventral Attention Network (VAN), Cingulo-Opercular Network (CON) and amygdala, all of which are networks shown to be associated with ELA. We used linear regression to examine associations between activation and ELA: negative parenting, social status, financial insecurity, neighborhood disadvantage, negative experiences, and parent psychopathology.</div></div><div><h3>Results</h3><div>We found DMN, VAN, CON and amygdala activation during sad/emotional, bonding, action, conflict, sad, or fearful scenes. Greater inconsistent discipline was associated with greater VAN activation during sad or emotional scenes.</div></div><div><h3>Conclusion</h3><div>Findings suggest that the DMN, VAN, CON networks and the amygdala support socio-emotional processing consistent with prior literature. Individuals who experienced inconsistent discipline may have greater sensitivity to parent–child separation signals. Since no other ELA–activation associations were found, it is possible that unpredictability may be more strongly associated with complex neural emotion processing than socio-economic status or negative life events.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101469"},"PeriodicalIF":4.6,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570027","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 : 2024-10-23DOI: 10.1016/j.dcn.2024.101467
Mohammad Ghasoub , Meaghan Perdue , Xiangyu Long , Claire Donnici , Preeti Kar , Ben Gibbard , Chris Tortorelli , Carly McMorris , Deborah Dewey , Catherine Lebel
Children with prenatal alcohol exposure (PAE) may develop a range of neurological and behavioral deficits, including reading and language disorders. Studying the brain’s structural connectivity and its relationship to pre-reading/reading skills in young children with PAE can help understand the roots of reading deficits associated with PAE. 363 diffusion MRI scans from 135 children (114 scans from 53 children with PAE) were collected between ages 3–7 years. Children completed NEPSY-II Phonological Processing and Speeded Naming to assess pre-reading skills at each scan. Structural brain network properties were assessed in 16 regions from both hemispheres using graph theory. Linear mixed models were used to account for repeated measures within participants. Children with PAE had significantly lower pre-reading scores than unexposed children, and significantly lower graph theory metrics across bilateral reading networks. Moreover, PAE significantly moderated the associations between Phonological Processing and global efficiency and nodal degree in the bilateral and left hemisphere reading networks, such that children with PAE had stronger associations than unexposed controls. No significant associations were found for Speeded Naming. Our results suggest that brain alterations may underlie early pre-reading difficulties in children with PAE.
{"title":"The brain’s structural connectivity and pre-reading abilities in young children with prenatal alcohol exposure","authors":"Mohammad Ghasoub , Meaghan Perdue , Xiangyu Long , Claire Donnici , Preeti Kar , Ben Gibbard , Chris Tortorelli , Carly McMorris , Deborah Dewey , Catherine Lebel","doi":"10.1016/j.dcn.2024.101467","DOIUrl":"10.1016/j.dcn.2024.101467","url":null,"abstract":"<div><div>Children with prenatal alcohol exposure (PAE) may develop a range of neurological and behavioral deficits, including reading and language disorders. Studying the brain’s structural connectivity and its relationship to pre-reading/reading skills in young children with PAE can help understand the roots of reading deficits associated with PAE. 363 diffusion MRI scans from 135 children (114 scans from 53 children with PAE) were collected between ages 3–7 years. Children completed NEPSY-II Phonological Processing and Speeded Naming to assess pre-reading skills at each scan. Structural brain network properties were assessed in 16 regions from both hemispheres using graph theory. Linear mixed models were used to account for repeated measures within participants. Children with PAE had significantly lower pre-reading scores than unexposed children, and significantly lower graph theory metrics across bilateral reading networks. Moreover, PAE significantly moderated the associations between Phonological Processing and global efficiency and nodal degree in the bilateral and left hemisphere reading networks, such that children with PAE had stronger associations than unexposed controls. No significant associations were found for Speeded Naming. Our results suggest that brain alterations may underlie early pre-reading difficulties in children with PAE.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101467"},"PeriodicalIF":4.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552624","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 : 2024-10-21DOI: 10.1016/j.dcn.2024.101460
Jenny Kingsley , Barbara Andraka-Christou , Seema K. Shah , Paul Spicer , Sharlene Newman , Pilar N. Ossorio , The HBCD ELP WG
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 HBCD study has faced several ethical and legal challenges due to its goal of enrolling pregnant people (including those with substance use disorder) and their newborns. Challenges not fully anticipated at the outset emerged from the rapidly changing legal landscape around reproductive rights in the United States. By embedding scholars in bioethics and law within research teams and engaging them in conversation with each other and other study personnel, we were able to address many challenges proactively and respond promptly to unanticipated challenges. In this paper, we highlight several important ethical and legal challenges that arose from the first phase of funding through the beginning of participant enrollment. We explain the methods used to address these challenges, the ethical and legal tradeoffs that arose, and the resolution of challenges through the design of the study. Based on this experience, we provide recommendations for research teams, sponsors, and reviewers to address legal risks and promote the ethical conduct of studies with pregnant people and caregivers. We highlight the importance of collaboration with bioethics and legal scholars in studies involving complex and evolving legal risks, as well as the necessity of designing robust approaches to informed consent and maintaining participant trust while navigating ethical challenges in research.
HEALthy Brain and Child Development（HBCD）研究是一项多站点前瞻性纵向队列研究，将从产前开始并计划到幼儿期对人类大脑、认知、行为、社交和情感发育进行研究。由于 HBCD 研究的目标是招募孕妇（包括药物滥用症患者）及其新生儿，因此面临着一些伦理和法律方面的挑战。由于美国围绕生殖权利的法律环境变化迅速，因此出现了一些一开始没有完全预料到的挑战。通过将生命伦理学和法学学者纳入研究团队，并让他们与其他研究人员相互交流，我们能够积极应对许多挑战，并对未预料到的挑战做出迅速反应。在本文中，我们将重点介绍从第一阶段筹资到开始招募参与者期间出现的几个重要的伦理和法律挑战。我们解释了应对这些挑战的方法、出现的伦理和法律权衡，以及通过研究设计解决挑战的方法。基于这些经验，我们为研究团队、申办者和评审人员提供了建议，以应对法律风险并促进孕妇和护理人员研究的伦理进行。我们强调了在涉及复杂和不断变化的法律风险的研究中与生命伦理学和法律学者合作的重要性，以及在应对研究中的伦理挑战时设计强有力的知情同意方法和维护参与者信任的必要性。
{"title":"Navigating ethical and legal challenges in the HEALthy Brain and Child Development Study: Lessons learned from the ethics, law, policy working group","authors":"Jenny Kingsley , Barbara Andraka-Christou , Seema K. Shah , Paul Spicer , Sharlene Newman , Pilar N. Ossorio , The HBCD ELP WG","doi":"10.1016/j.dcn.2024.101460","DOIUrl":"10.1016/j.dcn.2024.101460","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 HBCD study has faced several ethical and legal challenges due to its goal of enrolling pregnant people (including those with substance use disorder) and their newborns. Challenges not fully anticipated at the outset emerged from the rapidly changing legal landscape around reproductive rights in the United States. By embedding scholars in bioethics and law within research teams and engaging them in conversation with each other and other study personnel, we were able to address many challenges proactively and respond promptly to unanticipated challenges. In this paper, we highlight several important ethical and legal challenges that arose from the first phase of funding through the beginning of participant enrollment. We explain the methods used to address these challenges, the ethical and legal tradeoffs that arose, and the resolution of challenges through the design of the study. Based on this experience, we provide recommendations for research teams, sponsors, and reviewers to address legal risks and promote the ethical conduct of studies with pregnant people and caregivers. We highlight the importance of collaboration with bioethics and legal scholars in studies involving complex and evolving legal risks, as well as the necessity of designing robust approaches to informed consent and maintaining participant trust while navigating ethical challenges in research.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101460"},"PeriodicalIF":4.6,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142511334","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 : 2024-10-19DOI: 10.1016/j.dcn.2024.101465
Rachel Visontay , Lindsay M. Squeglia , Matthew Sunderland , Emma K. Devine , Hollie Byrne , Louise Mewton
Recent years have seen the increasing availability of large, population-based, longitudinal neuroimaging datasets, providing unprecedented capacity to examine brain-behavior relationships in the neurodevelopmental context. However, the ability of these datasets to deliver causal insights into brain-behavior relationships relies on the application of purpose-built analysis methods to counter the biases that otherwise preclude causal inference from observational data. Here we introduce these approaches (i.e., propensity score-based methods, the ‘G-methods’, targeted maximum likelihood estimation, and causal mediation analysis) and conduct a review to determine the extent to which they have been applied thus far in the field of developmental cognitive neuroscience. We identify just eight relevant studies, most of which employ propensity score-based methods. Many approaches are entirely absent from the literature, particularly those that promote causal inference in settings with complex, multi-wave data and repeated neuroimaging assessments. Causality is central to an etiological understanding of the relationship between the brain and behavior, as well as for identifying targets for prevention and intervention. Careful application of methods for causal inference may help the field of developmental cognitive neuroscience approach these goals.
{"title":"Enhancing causal inference in population-based neuroimaging data in children and adolescents","authors":"Rachel Visontay , Lindsay M. Squeglia , Matthew Sunderland , Emma K. Devine , Hollie Byrne , Louise Mewton","doi":"10.1016/j.dcn.2024.101465","DOIUrl":"10.1016/j.dcn.2024.101465","url":null,"abstract":"<div><div>Recent years have seen the increasing availability of large, population-based, longitudinal neuroimaging datasets, providing unprecedented capacity to examine brain-behavior relationships in the neurodevelopmental context. However, the ability of these datasets to deliver <em>causal</em> insights into brain-behavior relationships relies on the application of purpose-built analysis methods to counter the biases that otherwise preclude causal inference from observational data. Here we introduce these approaches (i.e., propensity score-based methods, the ‘G-methods’, targeted maximum likelihood estimation, and causal mediation analysis) and conduct a review to determine the extent to which they have been applied thus far in the field of developmental cognitive neuroscience. We identify just eight relevant studies, most of which employ propensity score-based methods. Many approaches are entirely absent from the literature, particularly those that promote causal inference in settings with complex, multi-wave data and repeated neuroimaging assessments. Causality is central to an etiological understanding of the relationship between the brain and behavior, as well as for identifying targets for prevention and intervention. Careful application of methods for causal inference may help the field of developmental cognitive neuroscience approach these goals.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101465"},"PeriodicalIF":4.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142511333","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 : 2024-10-18DOI: 10.1016/j.dcn.2024.101463
Lotte H. van Rijn , Suzanne van de Groep , Michelle Achterberg , Lara Wierenga , Barbara R. Braams , Valeria Gazzola , Berna Güroğlu , Christian Keysers , Lucres Nauta-Jansen , Anna van Duijvenvoorde , Lydia Krabbendam , Eveline A. Crone
With age, adolescents increasingly demonstrate the ability to forgo immediate, smaller rewards in favor of larger delayed rewards, indicating reduced delay discounting. Adolescence is also a time of social reorientation, where decisions not only involve weighing immediate against future outcomes, but also consequences for self versus those for others. In this functional Magnetic Resonance Imaging study, we examined the neural correlates of immediate and delayed reward choices where the delayed outcomes could benefit self, friends, or unknown others. A total of 196 adolescent twins aged 14–17 completed a social delay discounting task, with fMRI data acquired from 174 participants. Out of these, 156 adolescents had valid fMRI data, and 138 adolescents had observations in every condition. Adolescents more often chose the immediate reward when it was larger, and when the delay was longer. Area-under-the-curve (AUC) comparisons revealed that behavior differed across delay-beneficiaries, with AUC being highest for the self, followed by friends, and lowest for unknown others. This suggests that adolescents are more willing to wait for rewards for self. Neuroimaging analyses showed increased activity in the midline areas medial prefrontal cortex (MPFC) and precuneus, as well as bilateral temporal parietal junction (TPJ) when considering delayed reward for unknown others and friends compared to self. A whole-brain interaction with choice showed that the bilateral insula and right dorsolateral prefrontal cortex (DLPFC) were more active for delayed choices for unknown others and for immediate choices for friends and self. This underscores that the neuro-cognitive processing of how delays reduce the value of rewards depends on closeness of the beneficiary.
{"title":"Delay discounting in adolescence depends on whom you wait for: Evidence from a functional neuroimaging study","authors":"Lotte H. van Rijn , Suzanne van de Groep , Michelle Achterberg , Lara Wierenga , Barbara R. Braams , Valeria Gazzola , Berna Güroğlu , Christian Keysers , Lucres Nauta-Jansen , Anna van Duijvenvoorde , Lydia Krabbendam , Eveline A. Crone","doi":"10.1016/j.dcn.2024.101463","DOIUrl":"10.1016/j.dcn.2024.101463","url":null,"abstract":"<div><div>With age, adolescents increasingly demonstrate the ability to forgo immediate, smaller rewards in favor of larger delayed rewards, indicating reduced delay discounting. Adolescence is also a time of social reorientation, where decisions not only involve weighing immediate against future outcomes, but also consequences for self versus those for others. In this functional Magnetic Resonance Imaging study, we examined the neural correlates of immediate and delayed reward choices where the delayed outcomes could benefit self, friends, or unknown others. A total of 196 adolescent twins aged 14–17 completed a social delay discounting task, with fMRI data acquired from 174 participants. Out of these, 156 adolescents had valid fMRI data, and 138 adolescents had observations in every condition. Adolescents more often chose the immediate reward when it was larger, and when the delay was longer. Area-under-the-curve (AUC) comparisons revealed that behavior differed across delay-beneficiaries, with AUC being highest for the self, followed by friends, and lowest for unknown others. This suggests that adolescents are more willing to wait for rewards for self. Neuroimaging analyses showed increased activity in the midline areas medial prefrontal cortex (MPFC) and precuneus, as well as bilateral temporal parietal junction (TPJ) when considering delayed reward for unknown others and friends compared to self. A whole-brain interaction with choice showed that the bilateral insula and right dorsolateral prefrontal cortex (DLPFC) were more active for delayed choices for unknown others and for immediate choices for friends and self. This underscores that the neuro-cognitive processing of how delays reduce the value of rewards depends on closeness of the beneficiary.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"70 ","pages":"Article 101463"},"PeriodicalIF":4.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578546","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 : 2024-10-18DOI: 10.1016/j.dcn.2024.101466
Sandra A Brown, Hugh Garavan, Terry L Jernigan, Susan F Tapert, Rebekah S Huber, Daniel Lopez, Traci Murray, Gayathri Dowling, Elizabeth A Hoffman, Lucina Q Uddin
This editorial focuses on the issue of data misuse which is increasingly evidenced in social media as well as some premiere scientific journals. This issue is of critical importance to open science projects in general, and ABCD in particular, given the broad array of biological, behavioral and environmental information collected on this American sample of 12.000 youth and parents. ABCD data are already widely used with over 1000 publications and twice as many citations per year as expected (relative citation index based on year, field and journal). However, the adverse consequences of misuse of data, and inaccurate interpretation of emergent findings from this precedent setting study may have profound impact on disadvantaged populations and perpetuate biases and societal injustices.
{"title":"Responsible use of population neuroscience data: Towards standards of accountability and integrity.","authors":"Sandra A Brown, Hugh Garavan, Terry L Jernigan, Susan F Tapert, Rebekah S Huber, Daniel Lopez, Traci Murray, Gayathri Dowling, Elizabeth A Hoffman, Lucina Q Uddin","doi":"10.1016/j.dcn.2024.101466","DOIUrl":"https://doi.org/10.1016/j.dcn.2024.101466","url":null,"abstract":"<p><p>This editorial focuses on the issue of data misuse which is increasingly evidenced in social media as well as some premiere scientific journals. This issue is of critical importance to open science projects in general, and ABCD in particular, given the broad array of biological, behavioral and environmental information collected on this American sample of 12.000 youth and parents. ABCD data are already widely used with over 1000 publications and twice as many citations per year as expected (relative citation index based on year, field and journal). However, the adverse consequences of misuse of data, and inaccurate interpretation of emergent findings from this precedent setting study may have profound impact on disadvantaged populations and perpetuate biases and societal injustices.</p>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":" ","pages":"101466"},"PeriodicalIF":4.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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}
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