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Church JA. The Brain's Control Networks in Reading: Insights From Cross-Task Studies of Youth. MIND, BRAIN AND EDUCATION : THE OFFICIAL JOURNAL OF THE INTERNATIONAL MIND, BRAIN, AND EDUCATION SOCIETY 2023; 17:257-266. [PMID: 38745918 PMCID: PMC11091959 DOI: 10.1111/mbe.12372] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 06/04/2023] [Indexed: 05/16/2024]
Abstract
Humans engage multiple brain systems to read successfully, including using regions important for vision, language, and control. Control refers to the set of executive processes in the brain that guide moment-to-moment behavior in service of our goals. There is a growing appreciation for the role of the brain's control system in reading comprehension, in reading skill change over time, and in those who have difficulty with the reading process. One way to understand the brain's control engagement in reading may be to study control engagement across multiple tasks in order to study consistencies, or cross-task similarities, relative to reading-specific variations. In this commentary, I briefly summarize some of our recent work studying the brain's control networks across different tasks (e.g., when reading, or doing different executive function tasks). I then review our findings of when control activation does or does not relate to measures of reading ability, and reading growth over time. The utility of cross-task comparisons in neuroimaging is noted, as well as the need to better understand multiple sources of heterogeneity in our developmental samples. I end by discussing a few of the many future directions for further study of the brain with regard to the brain's control processing and academic achievement.
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Conte S, Richards JE, Fox NA, Valadez EA, McSweeney M, Tan E, Pine DS, Winkler AM, Liuzzi L, Cardinale EM, White LK, Buzzell GA. Multimodal study of the neural sources of error monitoring in adolescents and adults. Psychophysiology 2023; 60:e14336. [PMID: 37212619 PMCID: PMC10524909 DOI: 10.1111/psyp.14336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 04/16/2023] [Accepted: 05/01/2023] [Indexed: 05/23/2023]
Abstract
The ability to monitor performance during a goal-directed behavior differs among children and adults in ways that can be measured with several tasks and techniques. As well, recent work has shown that individual differences in error monitoring moderate temperamental risk for anxiety and that this moderation changes with age. We investigated age differences in neural responses linked to performance monitoring using a multimodal approach. The approach combined functional MRI and source localization of event-related potentials (ERPs) in 12-year-old, 15-year-old, and adult participants. Neural generators of two components related to performance and error monitoring, the N2 and ERN, lay within specific areas of fMRI clusters. Whereas correlates of the N2 component appeared similar across age groups, age-related differences manifested in the location of the generators of the ERN component. The dorsal anterior cingulate cortex (dACC) was the predominant source location for the 12-year-old group; this area manifested posteriorly for the 15-year-old and adult groups. A fMRI-based ROI analysis confirmed this pattern of activity. These results suggest that changes in the underlying neural mechanisms are related to developmental changes in performance monitoring.
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Affiliation(s)
- Stefania Conte
- Department of Psychology, University of South Carolina, Columbia, South Carolina, USA
| | - John E Richards
- Department of Psychology, University of South Carolina, Columbia, South Carolina, USA
| | - Nathan A Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Emilio A Valadez
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Marco McSweeney
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Enda Tan
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Daniel S Pine
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Anderson M Winkler
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Lucrezia Liuzzi
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Elise M Cardinale
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Lauren K White
- Lifespan Brain Institute of the Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania, USA
| | - George A Buzzell
- Florida International University and the Center for Children and Families, Miami, Florida, USA
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Rapuano KM, Tejavibulya L, Dinc EN, Li A, Davis H, Korn R, Leibel RL, Walsh BT, Ranzenhofer L, Rosenbaum M, Casey BJ, Mayer L. Heightened sensitivity to high-calorie foods in children at risk for obesity: insights from behavior, neuroimaging, and genetics. Brain Imaging Behav 2023; 17:461-470. [PMID: 37145386 PMCID: PMC10543571 DOI: 10.1007/s11682-023-00773-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/28/2023] [Indexed: 05/06/2023]
Abstract
Pediatric obesity is a major public health concern. Genetic susceptibility and increased availability of energy-dense food are known risk factors for obesity. However, the extent to which these factors jointly bias behavior and neural circuitry towards increased adiposity in children remains unclear. While undergoing fMRI, 108 children (ages 5-11y) performed a food-specific go/no-go task. Participants were instructed to either respond ("go") or inhibit responding ("no-go") to images of food or toys. Half of the runs depicted high-calorie foods (e.g., pizza) whereas the other half depicted low-calorie foods (e.g., salad). Children were also genotyped for a DNA polymorphism associated with energy intake and obesity (FTO rs9939609) to examine the influence of obesity risk on behavioral and brain responses to food. Participants demonstrated differences in behavioral sensitivity to high- and low-calorie food images depending on task demands. Participants were slower but more accurate at detecting high- (relative to low-) calorie foods when responding to a neutral stimulus (i.e., toys) and worse at detecting toys when responding to high-calorie foods. Inhibition failures were accompanied by salience network activity (anterior insula, dorsal anterior cingulate cortex), which was driven by false alarms to food images. Children at a greater genetic risk for obesity (dose-dependent model of the FTO genotype) demonstrated pronounced brain and behavioral relationships such that genetic risk was associated with heightened sensitivity to high-calorie food images and increased anterior insula activity. These findings suggest that high-calorie foods may be particularly salient to children at risk for developing eating habits that promote obesity.
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Affiliation(s)
- Kristina M Rapuano
- Department of Psychology, Yale University, 2 Hillhouse Ave, New Haven, CT, 06511, USA.
| | - Link Tejavibulya
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Eda Naz Dinc
- Department of Psychology, Yale University, 2 Hillhouse Ave, New Haven, CT, 06511, USA
| | - Anfei Li
- Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA
| | - Haley Davis
- Department of Psychiatry, Columbia University Medical College, New York, NY, USA
| | - Rachel Korn
- Department of Psychiatry, Columbia University Medical College, New York, NY, USA
| | - Rudolph L Leibel
- Department of Pediatrics, Columbia University Medical College, New York, NY, USA
| | - B Timothy Walsh
- Department of Psychiatry, Columbia University Medical College, New York, NY, USA
| | - Lisa Ranzenhofer
- Department of Psychiatry, Columbia University Medical College, New York, NY, USA
| | - Michael Rosenbaum
- Department of Pediatrics, Columbia University Medical College, New York, NY, USA
| | - B J Casey
- Department of Psychology, Yale University, 2 Hillhouse Ave, New Haven, CT, 06511, USA
| | - Laurel Mayer
- Department of Psychiatry, Columbia University Medical College, New York, NY, USA
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Nielsen AN, Kaplan S, Meyer D, Alexopoulos D, Kenley JK, Smyser TA, Wakschlag LS, Norton ES, Raghuraman N, Warner BB, Shimony JS, Luby JL, Neil JJ, Petersen SE, Barch DM, Rogers CE, Sylvester CM, Smyser CD. Maturation of large-scale brain systems over the first month of life. Cereb Cortex 2023; 33:2788-2803. [PMID: 35750056 PMCID: PMC10016041 DOI: 10.1093/cercor/bhac242] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 04/29/2022] [Accepted: 05/23/2022] [Indexed: 01/14/2023] Open
Abstract
The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.
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Affiliation(s)
- Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dominique Meyer
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeanette K Kenley
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Tara A Smyser
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Lauren S Wakschlag
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Feinberg School of Medicine, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Elizabeth S Norton
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Nandini Raghuraman
- Department of Obstetrics and Gynecology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joshua S Shimony
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeffery J Neil
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Cynthia E Rogers
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
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Davis BR, Garza A, Church JA. Key considerations for child and adolescent MRI data collection. FRONTIERS IN NEUROIMAGING 2022; 1:981947. [PMID: 36312216 PMCID: PMC9615104 DOI: 10.3389/fnimg.2022.981947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 08/16/2022] [Indexed: 11/15/2022]
Abstract
Cognitive neuroimaging researchers' ability to infer accurate statistical conclusions from neuroimaging depends greatly on the quality of the data analyzed. This need for quality control is never more evident than when conducting neuroimaging studies with children and adolescents. Developmental neuroimaging requires patience, flexibility, adaptability, extra time, and effort. It also provides us a unique, non-invasive way to understand the development of cognitive processes, individual differences, and the changing relations between brain and behavior over the lifespan. In this discussion, we focus on collecting magnetic resonance imaging (MRI) data, as it is one of the more complex protocols used with children and youth. Through our extensive experience collecting MRI datasets with children and families, as well as a review of current best practices, we will cover three main topics to help neuroimaging researchers collect high-quality datasets. First, we review key recruitment and retention techniques, and note the importance for consistency and inclusion across groups. Second, we discuss ways to reduce scan anxiety for families and ways to increase scan success by describing the pre-screening process, use of a scanner simulator, and the need to focus on participant and family comfort. Finally, we outline several important design considerations in developmental neuroimaging such as asking a developmentally appropriate question, minimizing data loss, and the applicability of public datasets. Altogether, we hope this article serves as a useful tool for those wishing to enter or learn more about developmental cognitive neuroscience.
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Affiliation(s)
| | | | - Jessica A. Church
- Department of Psychology, The University of Texas at Austin, Austin, TX, United States
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Weiss H, Luciana M. Neurobehavioral maturation of motor response inhibition in adolescence - A narrative review. Neurosci Biobehav Rev 2022; 137:104646. [PMID: 35367223 PMCID: PMC9119966 DOI: 10.1016/j.neubiorev.2022.104646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 02/19/2022] [Accepted: 03/28/2022] [Indexed: 11/17/2022]
Abstract
Immature motor response inhibition in adolescence is considered contributory to adolescent risk-taking and externalizing behaviors. We review studies reporting age-related variations in motor response inhibition and MRI measurements from typically-developing adolescents. Reviewed studies measured response inhibition using one of three tasks-the Stop Signal Task, Go/No-Go, and Antisaccade Task. Task reliability appears to be particularly strong for the SST. Across tasks and study designs, results indicate that inhibitory control improves markedly through early adolescence. The trajectory of change in later adolescence and into young adulthood (i.e., linear or plateauing) varies depending on the task design. Neuroimaging studies identify adult-like response inhibition networks that are involved in behavioral development. The pros and cons of each task are discussed, including recommendations to guide future studies. Ongoing studies in large longitudinal datasets offer opportunities for further exploration of the shape of change in response inhibition, related neural regions, and associations with other affective and cognitive processes to identify potential impacts of motor response inhibition immaturities or individual differences on adolescent risk-taking behaviors.
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Affiliation(s)
- Hannah Weiss
- Department of Psychology, University of Minnesota, Minneapolis, USA.
| | - Monica Luciana
- Department of Psychology, University of Minnesota, Minneapolis, USA
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Castelhano J, Duarte IC, Couceiro R, Medeiros J, Duraes J, Afonso S, Madeira H, Castelo-Branco M. Software Bug Detection Causes a Shift From Bottom-Up to Top-Down Effective Connectivity Involving the Insula Within the Error-Monitoring Network. Front Hum Neurosci 2022; 16:788272. [PMID: 35321263 PMCID: PMC8935015 DOI: 10.3389/fnhum.2022.788272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/07/2022] [Indexed: 11/14/2022] Open
Abstract
The neural correlates of software programming skills have been the target of an increasing number of studies in the past few years. Those studies focused on error-monitoring during software code inspection. Others have studied task-related cognitive load as measured by distinct neurophysiological measures. Most studies addressed only syntax errors (shallow level of code monitoring). However, a recent functional MRI (fMRI) study suggested a pivotal role of the insula during error-monitoring when challenging deep-level analysis of code inspection was required. This raised the hypothesis that the insula is causally involved in deep error-monitoring. To confirm this hypothesis, we carried out a new fMRI study where participants performed a deep source-code comprehension task that included error-monitoring to detect bugs in the code. The generality of our paradigm was enhanced by comparison with a variety of tasks related to text reading and bugless source-code understanding. Healthy adult programmers (N = 21) participated in this 3T fMRI experiment. The activation maps evoked by error-related events confirmed significant activations in the insula [p(Bonferroni) < 0.05]. Importantly, a posterior-to-anterior causality shift was observed concerning the role of the insula: in the absence of error, causal directions were mainly bottom-up, whereas, in their presence, the strong causal top-down effects from frontal regions, in particular, the anterior cingulate cortex was observed.
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Affiliation(s)
- Joao Castelhano
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT)/ICNAS, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Isabel C. Duarte
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT)/ICNAS, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Ricardo Couceiro
- CISUC-Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal
| | - Julio Medeiros
- CISUC-Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal
| | - Joao Duraes
- CISUC-Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal
- Coimbra Polytechnic—ISEC, Coimbra, Portugal
| | - Sónia Afonso
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT)/ICNAS, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Henrique Madeira
- CISUC-Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT)/ICNAS, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- *Correspondence: Miguel Castelo-Branco,
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