Pub Date : 2025-01-25DOI: 10.1016/j.dcn.2025.101513
John N. Constantino , Anna M. Constantino-Pettit
An irresistible but elusive promise of the field of developmental neuroimaging is to advance mechanistic understanding of neuropsychiatric conditions of childhood, toward translation to higher-impact intervention. In this article we wish to address a diversity of perspectives on that promise, which were expressed in a summarizing forum of the Fetal, Infant, and Toddler Neuroimaging Group (FIT’NG) conference in Santa Rosa, CA in September 2023. We organize our remarks according to three contemporary paradoxes: (1) the contrasting implications of neural correlates of development that reflect causes versus effects (or epiphenomena) of behavioral atypicality; (2) the interpretation of transient deviations in brain development that are associated with enduring developmental traits; and (3) the intensifying pursuit of discovery of neural correlates of behavior in an era of still-limited capacity to manipulate the course of early brain and behavioral development. In the article we leverage examples of recent advances in brain and behavioral science that help reconcile progress, skepticism, and hope as an emerging field matures and attracts new scientists into its ranks.
{"title":"Causation, trait correlation, and translation: Developmental brain imaging in research on neuropsychiatric conditions of childhood","authors":"John N. Constantino , Anna M. Constantino-Pettit","doi":"10.1016/j.dcn.2025.101513","DOIUrl":"10.1016/j.dcn.2025.101513","url":null,"abstract":"<div><div>An irresistible but elusive promise of the field of developmental neuroimaging is to advance mechanistic understanding of neuropsychiatric conditions of childhood, toward translation to higher-impact intervention. In this article we wish to address a diversity of perspectives on that promise, which were expressed in a summarizing forum of the Fetal, Infant, and Toddler Neuroimaging Group (FIT’NG) conference in Santa Rosa, CA in September 2023. We organize our remarks according to three contemporary paradoxes: (1) the contrasting implications of neural correlates of development that reflect causes versus effects (or <em>epiphenomena</em>) of behavioral atypicality; (2) the interpretation of transient deviations in brain development that are associated with enduring developmental traits; and (3) the intensifying pursuit of discovery of neural correlates of behavior in an era of still-limited capacity to manipulate the course of early brain and behavioral development. In the article we leverage examples of recent advances in brain and behavioral science that help reconcile progress, skepticism, and hope as an emerging field matures and attracts new scientists into its ranks.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101513"},"PeriodicalIF":4.6,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143152632","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 : 2025-01-25DOI: 10.1016/j.dcn.2025.101520
Lisa Bruckert , Garikoitz Lerma-Usabiaga , Lauren R. Borchers , Virginia A. Marchman , Katherine E. Travis , Heidi M. Feldman
Purpose
To determine if reading development between ages 6 and 8 years related to changes in fractional anisotropy (FA) in the optic radiations (OR), and if these associations were similar in children born full term (FT) and preterm (PT) and in language tracts.
Methods
FT (n = 34) and PT (n = 34) children completed the Word Identification subtest of the Woodcock Reading Mastery Test at 6, 7, and 8 years. Diffusion MRI (96-directions, b=2500 sec/mm2) was acquired at 6 and 8 years. Probabilistic tractography identified bilateral OR and three left-hemisphere language tracts: inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and arcuate fasciculus (AF). Linear mixed models determined if FA changes in these tracts were associated with reading growth.
Results
Rates of reading growth were similar in both groups. For the OR, FA change from 6 to 8 years was negatively associated with reading growth in both groups. A similar pattern was observed in the left ILF but not in the SLF or AF.
Conclusion
Individual differences in reading development were associated with FA change of the OR and left ILF in FT and PT children. Negative associations implicate increasing axonal diameter and/or complexity in fiber structure as drivers of faster reading development.
{"title":"The optic radiations and reading development: A longitudinal study of children born term and preterm","authors":"Lisa Bruckert , Garikoitz Lerma-Usabiaga , Lauren R. Borchers , Virginia A. Marchman , Katherine E. Travis , Heidi M. Feldman","doi":"10.1016/j.dcn.2025.101520","DOIUrl":"10.1016/j.dcn.2025.101520","url":null,"abstract":"<div><h3>Purpose</h3><div>To determine if reading development between ages 6 and 8 years related to changes in fractional anisotropy (FA) in the optic radiations (OR), and if these associations were similar in children born full term (FT) and preterm (PT) and in language tracts.</div></div><div><h3>Methods</h3><div>FT (n = 34) and PT (n = 34) children completed the Word Identification subtest of the Woodcock Reading Mastery Test at 6, 7, and 8 years. Diffusion MRI (96-directions, b=2500 sec/mm<sup>2</sup>) was acquired at 6 and 8 years. Probabilistic tractography identified bilateral OR and three left-hemisphere language tracts: inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and arcuate fasciculus (AF). Linear mixed models determined if FA changes in these tracts were associated with reading growth.</div></div><div><h3>Results</h3><div>Rates of reading growth were similar in both groups. For the OR, FA change from 6 to 8 years was negatively associated with reading growth in both groups. A similar pattern was observed in the left ILF but not in the SLF or AF.</div></div><div><h3>Conclusion</h3><div>Individual differences in reading development were associated with FA change of the OR and left ILF in FT and PT children. Negative associations implicate increasing axonal diameter and/or complexity in fiber structure as drivers of faster reading development.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101520"},"PeriodicalIF":4.6,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143076087","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 : 2025-01-22DOI: 10.1016/j.dcn.2025.101519
Anne-Lise Marais, Nadege Roche-Labarbe
Sensory prediction and repetition suppression are closely related cognitive mechanisms that allow the brain to form predictions about the environment, and guide perception in synergy with attention. Predictive coding is a theory of the fundamental role of predictive mechanisms in brain functions. Authors have proposed a central role of predictive impairments in autism and possibly other neurodevelopmental disorders. However, little is known about predictive mechanisms in typical development, and how they co-develop with attention. Here we review experimental support for predictive coding and its links with attention in healthy adults’ brains, the first experimental works performed in typically developing children and infants, and theoretical accounts of neurodevelopmental disorders using a predictive coding framework. We propose future directions for predictive coding research in development. Finally, we describe the first predictive coding experiments in neonates and provide research perspectives for using this framework in searching for early markers of atypical neurodevelopment.
{"title":"Predictive coding and attention in developmental cognitive neuroscience and perspectives for neurodevelopmental disorders","authors":"Anne-Lise Marais, Nadege Roche-Labarbe","doi":"10.1016/j.dcn.2025.101519","DOIUrl":"10.1016/j.dcn.2025.101519","url":null,"abstract":"<div><div>Sensory prediction and repetition suppression are closely related cognitive mechanisms that allow the brain to form predictions about the environment, and guide perception in synergy with attention. Predictive coding is a theory of the fundamental role of predictive mechanisms in brain functions. Authors have proposed a central role of predictive impairments in autism and possibly other neurodevelopmental disorders. However, little is known about predictive mechanisms in typical development, and how they co-develop with attention. Here we review experimental support for predictive coding and its links with attention in healthy adults’ brains, the first experimental works performed in typically developing children and infants, and theoretical accounts of neurodevelopmental disorders using a predictive coding framework. We propose future directions for predictive coding research in development. Finally, we describe the first predictive coding experiments in neonates and provide research perspectives for using this framework in searching for early markers of atypical neurodevelopment.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101519"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048395","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 : 2025-01-21DOI: 10.1016/j.dcn.2025.101511
Suzanne van de Groep, Sophie W Sweijen, Erik de Water, Eveline A Crone
{"title":"Corrigendum to \"Temporal discounting for self and friends in adolescence: A fMRI study\" [Dev. Cogn. Neurosci. 60 (2023) 1-11: 101204].","authors":"Suzanne van de Groep, Sophie W Sweijen, Erik de Water, Eveline A Crone","doi":"10.1016/j.dcn.2025.101511","DOIUrl":"https://doi.org/10.1016/j.dcn.2025.101511","url":null,"abstract":"","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":" ","pages":"101511"},"PeriodicalIF":4.6,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143025029","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 : 2025-01-16DOI: 10.1016/j.dcn.2025.101512
Jessica V. Schaaf , Steven Miletić , Anna C.K. van Duijvenvoorde , Hilde M. Huizenga
Computational neuroscience offers a valuable opportunity to understand the neural mechanisms underlying behavior. However, interpreting individual differences in these mechanisms, such as developmental differences, is less straightforward. We illustrate this challenge through studies that examine individual differences in reinforcement learning. In these studies, a computational model generates an individual-specific prediction error regressor to model activity in a brain region of interest. Individual differences in the resulting regression weight are typically interpreted as individual differences in neural coding. We first demonstrate that the absence of individual differences in neural coding is not problematic, as such differences are already captured in the individual specific regressor. We then review that the presence of individual differences is typically interpreted as individual differences in the use of brain resources. However, through simulations, we illustrate that these differences could also stem from other factors such as the standardization of the prediction error, individual differences in brain networks outside the region of interest, individual differences in the duration of the prediction error response, individual differences in outcome valuation, and in overlooked individual differences in computational model parameters or the type of computational model. To clarify these interpretations, we provide several recommendations. In this manner we aim to advance the understanding and interpretation of individual differences in computational neuroscience.
{"title":"Interpretation of individual differences in computational neuroscience using a latent input approach","authors":"Jessica V. Schaaf , Steven Miletić , Anna C.K. van Duijvenvoorde , Hilde M. Huizenga","doi":"10.1016/j.dcn.2025.101512","DOIUrl":"10.1016/j.dcn.2025.101512","url":null,"abstract":"<div><div>Computational neuroscience offers a valuable opportunity to understand the neural mechanisms underlying behavior. However, interpreting individual differences in these mechanisms, such as developmental differences, is less straightforward. We illustrate this challenge through studies that examine individual differences in reinforcement learning. In these studies, a computational model generates an individual-specific prediction error regressor to model activity in a brain region of interest. Individual differences in the resulting regression weight are typically interpreted as individual differences in neural coding. We first demonstrate that the <em>absence</em> of individual differences in neural coding is not problematic, as such differences are already captured in the individual specific regressor. We then review that the <em>presence</em> of individual differences is typically interpreted as individual differences in the use of brain resources. However, through simulations, we illustrate that these differences could also stem from other factors such as the standardization of the prediction error, individual differences in brain networks outside the region of interest, individual differences in the duration of the prediction error response, individual differences in outcome valuation, and in overlooked individual differences in computational model parameters or the type of computational model. To clarify these interpretations, we provide several recommendations. In this manner we aim to advance the understanding and interpretation of individual differences in computational neuroscience.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101512"},"PeriodicalIF":4.6,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143042998","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 : 2025-01-11DOI: 10.1016/j.dcn.2025.101508
H. Yang , JW. Cohen , D. Pagliaccio , B. Ramphal , V. Rauh , F. Perera , BS. Peterson , H. Andrews , AG. Rundle , J. Herbstman , AE. Margolis
Reading difficulties and exposure to air pollution are both disproportionately high among youth living in economically disadvantaged contexts. Critically, variance in reading skills in youth living in higher socioeconomic status (SES) contexts largely derives from genetic factors, whereas environmental factors explain more of the variance in reading skills among youth living in lower SES contexts. Although reading research has focused closely on the psychosocial environment, little focus has been paid to the effects of the chemical environment. In this study, we measured prenatal exposure to a common air pollutant, polycyclic aromatic hydrocarbons (PAH), via the presence (versus absence) of PAH-DNA adducts in maternal blood during the third trimester of pregnancy. We examined the impact of prenatal PAH exposure on adolescent hippocampal subfield volume and on word reading in a sample of youth followed prospectively since birth (N = 165). Compared to those without prenatal exposure, those with detectable PAH-DNA adducts (N = 63) exhibited significantly smaller hippocampal volumes (CA2/3 subfield, t = -2.413, p < .05), which was associated with worse pseudoword reading (t = 2.346, p < .05). Exploratory mediation analyses showed a significant effect of PAH on pseudoword reading through CA2/3 vol (p = .028), suggesting that prenatal PAH exposure affects hippocampal volume with downstream effects on reading ability.
{"title":"Prenatal exposure to polycyclic aromatic hydrocarbons, reduced hippocampal subfield volumes, and word reading","authors":"H. Yang , JW. Cohen , D. Pagliaccio , B. Ramphal , V. Rauh , F. Perera , BS. Peterson , H. Andrews , AG. Rundle , J. Herbstman , AE. Margolis","doi":"10.1016/j.dcn.2025.101508","DOIUrl":"10.1016/j.dcn.2025.101508","url":null,"abstract":"<div><div>Reading difficulties and exposure to air pollution are both disproportionately high among youth living in economically disadvantaged contexts. Critically, variance in reading skills in youth living in higher socioeconomic status (SES) contexts largely derives from genetic factors, whereas environmental factors explain more of the variance in reading skills among youth living in lower SES contexts. Although reading research has focused closely on the psychosocial environment, little focus has been paid to the effects of the chemical environment. In this study, we measured prenatal exposure to a common air pollutant, polycyclic aromatic hydrocarbons (PAH), via the presence (versus absence) of PAH-DNA adducts in maternal blood during the third trimester of pregnancy. We examined the impact of prenatal PAH exposure on adolescent hippocampal subfield volume and on word reading in a sample of youth followed prospectively since birth (N = 165). Compared to those without prenatal exposure, those with detectable PAH-DNA adducts (N = 63) exhibited significantly smaller hippocampal volumes (CA2/3 subfield, <em>t</em> = -2.413, <em>p</em> < .05), which was associated with worse pseudoword reading (<em>t</em> = 2.346, <em>p</em> < .05). Ex<em>p</em>loratory mediation analyses showed a significant effect of PAH on pseudoword reading through CA2/3 vol (<em>p</em> = .028), suggesting that prenatal PAH exposure affects hippocampal volume with downstream effects on reading ability.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101508"},"PeriodicalIF":4.6,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014668","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 : 2025-01-10DOI: 10.1016/j.dcn.2025.101510
Isabella Starling-Alves , Lien Peters , Eric D. Wilkey
Mathematics learning disorders (MD) and reading learning disorders (RD) are persistent conditions that interfere with success in academic and daily-life tasks, and cannot be attributed to intellectual disabilities, sensory deficits, or environmental factors. Prevalence rates of MD and RD are estimated at 5–10 % of school-age children, and their comorbidity (MDRD) is highly prevalent, with around 40 % of children with MD also experiencing RD. Despite this high comorbidity rate, research on MDRD has received less attention compared to isolated conditions, leaving its neurocognitive mechanisms unclear. In this study, we review behavioral, neuroimaging, and genetic MDRD research and discuss how they support current MDRD models, including the: (1) additive model, which proposes that MDRD results from the addition of neurocognitive deficits unique to MD or RD, (2) domain-general deficits model, which proposes that MDRD stems from executive function deficits, and (3) increased risk model, which proposes that MDRD emerges from phonological deficits characteristic of RD. Further, we recommend updating models of MDRD by integrating the multiple deficit and dimensional models to build a unified framework for research and diagnosis that considers multiple dimensions of mathematics, reading, and domain-general skills. This unified framework highlights the importance of a holistic, functional diagnosis.
{"title":"Beyond the sum of their parts: A multi-dimensional approach to dyscalculia-dyslexia comorbidity integrating studies of the brain, behavior, and genetics","authors":"Isabella Starling-Alves , Lien Peters , Eric D. Wilkey","doi":"10.1016/j.dcn.2025.101510","DOIUrl":"10.1016/j.dcn.2025.101510","url":null,"abstract":"<div><div>Mathematics learning disorders (MD) and reading learning disorders (RD) are persistent conditions that interfere with success in academic and daily-life tasks, and cannot be attributed to intellectual disabilities, sensory deficits, or environmental factors. Prevalence rates of MD and RD are estimated at 5–10 % of school-age children, and their comorbidity (MDRD) is highly prevalent, with around 40 % of children with MD also experiencing RD. Despite this high comorbidity rate, research on MDRD has received less attention compared to isolated conditions, leaving its neurocognitive mechanisms unclear. In this study, we review behavioral, neuroimaging, and genetic MDRD research and discuss how they support current MDRD models, including the: (1) additive model, which proposes that MDRD results from the addition of neurocognitive deficits unique to MD or RD, (2) domain-general deficits model, which proposes that MDRD stems from executive function deficits, and (3) increased risk model, which proposes that MDRD emerges from phonological deficits characteristic of RD. Further, we recommend updating models of MDRD by integrating the multiple deficit and dimensional models to build a unified framework for research and diagnosis that considers multiple dimensions of mathematics, reading, and domain-general skills. This unified framework highlights the importance of a holistic, functional diagnosis.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101510"},"PeriodicalIF":4.6,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014655","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 : 2025-01-09DOI: 10.1016/j.dcn.2025.101506
Carlijn van den Boomen, Anna C. Praat, Caroline M.M. Junge, Chantal Kemner
In response to Covid-19, western governments introduced policies that likely resulted in a reduced variety of facial input. This study investigated how this affected neural representations of face processing: speed of face processing; face categorization (differentiating faces from houses); and emotional face processing (differentiating happy, fearful, and neutral expressions), in infants (five or ten months old) and children (three years old). We compared participants tested before (total N = 462) versus during (total N = 473) the pandemic-related policies, and used electroencephalography to record brain activity. Event Related Potentials showed faster face processing in three-year-olds but not in infants during the policies. However, there were no meaningful differences between the two Covid-groups regarding face categorization, indicating that this fundamental process is resilient despite the reduced variety of input. In contrast, the processing of facial emotions was affected: across ages, while pre-pandemic children showed differential activity, during-pandemic children did not neurocognitively differentiate between happy and fearful expressions. This effect was primarily attributed to a reduced amplitude in response to happy faces. Given that these findings were present only in the later neural components (P400 and Nc), this suggests that post-pandemic children have a reduced familiarity or attention towards happy facial expressions.
{"title":"The effects of Covid-19 related policies on neurocognitive face processing in the first four years of life","authors":"Carlijn van den Boomen, Anna C. Praat, Caroline M.M. Junge, Chantal Kemner","doi":"10.1016/j.dcn.2025.101506","DOIUrl":"10.1016/j.dcn.2025.101506","url":null,"abstract":"<div><div>In response to Covid-19, western governments introduced policies that likely resulted in a reduced variety of facial input. This study investigated how this affected neural representations of face processing: speed of face processing; face categorization (differentiating faces from houses); and emotional face processing (differentiating happy, fearful, and neutral expressions), in infants (five or ten months old) and children (three years old). We compared participants tested before (total N = 462) versus during (total N = 473) the pandemic-related policies, and used electroencephalography to record brain activity. Event Related Potentials showed faster face processing in three-year-olds but not in infants during the policies. However, there were no meaningful differences between the two Covid-groups regarding face categorization, indicating that this fundamental process is resilient despite the reduced variety of input. In contrast, the processing of facial emotions was affected: across ages, while pre-pandemic children showed differential activity, during-pandemic children did not neurocognitively differentiate between happy and fearful expressions. This effect was primarily attributed to a reduced amplitude in response to happy faces. Given that these findings were present only in the later neural components (P400 and Nc), this suggests that post-pandemic children have a reduced familiarity or attention towards happy facial expressions.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101506"},"PeriodicalIF":4.6,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787029/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014670","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 : 2025-01-03DOI: 10.1016/j.dcn.2024.101505
Emma T. Margolis , Paige M. Nelson , Abigail Fiske , Juliette L.Y. Champaud , Halie A. Olson , María José C. Gomez , Áine T. Dineen , Chiara Bulgarelli , Sonya V. Troller-Renfree , Kirsten A. Donald , Marisa N. Spann , Brittany Howell , Dustin Scheinost , Marta Korom
Fetal, infant, and toddler (FIT) neuroimaging researchers study early brain development to gain insights into neurodevelopmental processes and identify early markers of neurobiological vulnerabilities to target for intervention. However, the field has historically excluded people from global majority countries and from marginalized communities in FIT neuroimaging research. Inclusive and representative samples are essential for generalizing findings across neuroimaging modalities, such as magnetic resonance imaging, magnetoencephalography, electroencephalography, functional near-infrared spectroscopy, and cranial ultrasonography. These FIT neuroimaging techniques pose unique and overlapping challenges to equitable representation in research through sampling bias, technical constraints, limited accessibility, and insufficient resources. The present article adds to the conversation around the need to improve inclusivity by highlighting modality-specific historical and current obstacles and ongoing initiatives. We conclude by discussing tangible solutions that transcend individual modalities, ultimately providing recommendations to promote equitable FIT neuroscience.
{"title":"Modality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples","authors":"Emma T. Margolis , Paige M. Nelson , Abigail Fiske , Juliette L.Y. Champaud , Halie A. Olson , María José C. Gomez , Áine T. Dineen , Chiara Bulgarelli , Sonya V. Troller-Renfree , Kirsten A. Donald , Marisa N. Spann , Brittany Howell , Dustin Scheinost , Marta Korom","doi":"10.1016/j.dcn.2024.101505","DOIUrl":"10.1016/j.dcn.2024.101505","url":null,"abstract":"<div><div>Fetal, infant, and toddler (FIT) neuroimaging researchers study early brain development to gain insights into neurodevelopmental processes and identify early markers of neurobiological vulnerabilities to target for intervention. However, the field has historically excluded people from global majority countries and from marginalized communities in FIT neuroimaging research. Inclusive and representative samples are essential for generalizing findings across neuroimaging modalities, such as magnetic resonance imaging, magnetoencephalography, electroencephalography, functional near-infrared spectroscopy, and cranial ultrasonography. These FIT neuroimaging techniques pose unique and overlapping challenges to equitable representation in research through sampling bias, technical constraints, limited accessibility, and insufficient resources. The present article adds to the conversation around the need to improve inclusivity by highlighting modality-specific historical and current obstacles and ongoing initiatives. We conclude by discussing tangible solutions that transcend individual modalities, ultimately providing recommendations to promote equitable FIT neuroscience.</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"72 ","pages":"Article 101505"},"PeriodicalIF":4.6,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402890","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 : 2025-01-01DOI: 10.1016/j.dcn.2024.101490
Koraly Pérez-Edgar , Mary Dozier , Rebecca Saxe , Katherine E. MacDuffie
Successful developmental neuroimaging efforts require interdisciplinary expertise to ground scientific questions in knowledge of human development, modify and create technologies and data processing pipelines suited to the young brain, and ensure research procedures meet the needs and protect the interests of young children and their caregivers. This paper brings together four interdisciplinary perspectives to tackle a set of questions that are central for the field to address as we imagine a future role for developmental neuroimaging in the prediction of neurodevelopmental or psychiatric disorders: 1) How do we generate a strong evidence base for causality and clinical relevance? 2) How do we ensure the integrity of the data and support fair and wide access? 3) How can these technologies be implemented in the clinic? 4) What are the ethical obligations for neuroimaging researchers working with infants and young children?
{"title":"How will developmental neuroimaging contribute to the prediction of neurodevelopmental or psychiatric disorders? Challenges and opportunities","authors":"Koraly Pérez-Edgar , Mary Dozier , Rebecca Saxe , Katherine E. MacDuffie","doi":"10.1016/j.dcn.2024.101490","DOIUrl":"10.1016/j.dcn.2024.101490","url":null,"abstract":"<div><div>Successful developmental neuroimaging efforts require interdisciplinary expertise to ground scientific questions in knowledge of human development, modify and create technologies and data processing pipelines suited to the young brain, and ensure research procedures meet the needs and protect the interests of young children and their caregivers. This paper brings together four interdisciplinary perspectives to tackle a set of questions that are central for the field to address as we imagine a future role for developmental neuroimaging in the prediction of neurodevelopmental or psychiatric disorders: 1) How do we generate a strong evidence base for causality and clinical relevance? 2) How do we ensure the integrity of the data and support fair and wide access? 3) How can these technologies be implemented in the clinic? 4) What are the ethical obligations for neuroimaging researchers working with infants and young children?</div></div>","PeriodicalId":49083,"journal":{"name":"Developmental Cognitive Neuroscience","volume":"71 ","pages":"Article 101490"},"PeriodicalIF":4.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11721882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865884","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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