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Katia D. Howlett

Other affiliations: National Institutes of Health
Bio: Katia D. Howlett is an academic researcher from National Institute on Drug Abuse. The author has contributed to research in topics: Cognitive development & Cognition. The author has an hindex of 6, co-authored 11 publications receiving 552 citations. Previous affiliations of Katia D. Howlett include National Institutes of Health.

Papers
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Journal ArticleDOI
Donald J. Hagler1, Sean N. Hatton1, M. Daniela Cornejo1, Carolina Makowski2, Damien A. Fair3, Anthony Steven Dick4, Matthew T. Sutherland4, B. J. Casey5, M Deanna6, Michael P. Harms6, Richard Watts5, James M. Bjork7, Hugh Garavan8, Laura Hilmer1, Christopher J. Pung1, Chelsea S. Sicat1, Joshua M. Kuperman1, Hauke Bartsch1, Feng Xue1, Mary M. Heitzeg9, Angela R. Laird4, Thanh T. Trinh1, Raul Gonzalez4, Susan F. Tapert1, Michael C. Riedel4, Lindsay M. Squeglia10, Luke W. Hyde9, Monica D. Rosenberg5, Eric Earl3, Katia D. Howlett11, Fiona C. Baker12, Mary E. Soules9, Jazmin Diaz1, Octavio Ruiz de Leon1, Wesley K. Thompson1, Michael C. Neale7, Megan M. Herting13, Elizabeth R. Sowell13, Ruben P. Alvarez11, Samuel W. Hawes4, Mariana Sanchez4, Jerzy Bodurka14, Florence J. Breslin14, Amanda Sheffield Morris14, Martin P. Paulus14, W. Kyle Simmons14, Jonathan R. Polimeni15, Andre van der Kouwe15, Andrew S. Nencka16, Kevin M. Gray10, Carlo Pierpaoli11, John A. Matochik11, Antonio Noronha11, Will M. Aklin11, Kevin P. Conway11, Meyer D. Glantz11, Elizabeth Hoffman11, Roger Little11, Marsha F. Lopez11, Vani Pariyadath11, Susan R.B. Weiss11, Dana L. Wolff-Hughes, Rebecca DelCarmen-Wiggins, Sarah W. Feldstein Ewing3, Oscar Miranda-Dominguez3, Bonnie J. Nagel3, Anders Perrone3, Darrick Sturgeon3, Aimee Goldstone12, Adolf Pfefferbaum12, Kilian M. Pohl12, Devin Prouty12, Kristina A. Uban17, Susan Y. Bookheimer18, Mirella Dapretto18, Adriana Galván18, Kara Bagot1, Jay N. Giedd1, M. Alejandra Infante1, Joanna Jacobus1, Kevin Patrick1, Paul D. Shilling1, Rahul S. Desikan19, Yi Li19, Leo P. Sugrue19, Marie T. Banich20, Naomi P. Friedman20, John K. Hewitt20, Christian J. Hopfer20, Joseph T. Sakai20, Jody Tanabe20, Linda B. Cottler21, Sara Jo Nixon21, Linda Chang22, Christine C. Cloak22, Thomas Ernst22, Gloria Reeves22, David N. Kennedy23, Steve Heeringa9, Scott Peltier9, John E. Schulenberg9, Chandra Sripada9, Robert A. Zucker9, William G. Iacono24, Monica Luciana24, Finnegan J. Calabro25, Duncan B. Clark25, David A. Lewis25, Beatriz Luna25, Claudiu Schirda25, Tufikameni Brima26, John J. Foxe26, Edward G. Freedman26, Daniel W. Mruzek26, Michael J. Mason27, Rebekah S. Huber28, Erin McGlade28, Andrew P. Prescot28, Perry F. Renshaw28, Deborah A. Yurgelun-Todd28, Nicholas Allgaier8, Julie A. Dumas8, Masha Y. Ivanova8, Alexandra Potter8, Paul Florsheim29, Christine L. Larson29, Krista M. Lisdahl29, Michael E. Charness30, Michael E. Charness15, Michael E. Charness31, Bernard F. Fuemmeler7, John M. Hettema7, Hermine H. Maes7, Joel L. Steinberg7, Andrey P. Anokhin6, Paul E.A. Glaser6, Andrew C. Heath6, Pamela A. F. Madden6, Arielle R. Baskin-Sommers5, R. Todd Constable5, Steven Grant11, Gayathri J. Dowling11, Sandra A. Brown1, Terry L. Jernigan1, Anders M. Dale1 
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the Adolescent Brain Cognitive Development Study are described to be a resource of unprecedented scale and depth for studying typical and atypical development.

431 citations

Posted ContentDOI
Donald J. Hagler1, Sean N. Hatton1, Carolina Makowski2, M. Daniela Cornejo3, Damien A. Fair3, Anthony Steven Dick4, Matthew T. Sutherland4, B. J. Casey5, M Deanna6, Michael P. Harms6, Richard Watts5, James M. Bjork7, Hugh Garavan8, Laura Hilmer1, Christopher J. Pung1, Chelsea S. Sicat1, Joshua M. Kuperman1, Hauke Bartsch1, Feng Xue1, Mary M. Heitzeg9, Angela R. Laird4, Thanh T. Trinh1, Raul Gonzalez4, Susan F. Tapert1, Michael C. Riedel4, Lindsay M. Squeglia10, Luke W. Hyde9, Monica D. Rosenberg5, Eric Earl3, Katia D. Howlett11, Fiona C. Baker12, Mary E. Soules9, Jazmin Diaz1, Octavio Ruiz de Leon1, Wesley K. Thompson1, Michael C. Neale7, Megan M. Herting13, Elizabeth R. Sowell13, Ruben P. Alvarez14, Samuel W. Hawes4, Mariana Sanchez4, Jerzy Bodurka15, Florence J. Breslin15, Amanda Sheffield Morris15, Martin P. Paulus15, W. Kyle Simmons15, Jonathan R. Polimeni16, Andre van der Kouwe16, Andrew S. Nencka17, Kevin M. Gray10, Carlo Pierpaoli14, John A. Matochik14, Antonio Noronha14, Will M. Aklin11, Kevin P. Conway11, Meyer D. Glantz11, Elizabeth Hoffman11, Roger Little11, Marsha F. Lopez11, Vani Pariyadath11, Susan R.B. Weiss11, Dana L. Wolff-Hughes, Rebecca DelCarmen-Wiggins, Sarah W. Feldstein Ewing3, Oscar Miranda-Dominguez3, Bonnie J. Nagel3, Anders Perrone3, Darrick Sturgeon3, Aimee Goldstone12, Adolf Pfefferbaum12, Kilian M. Pohl12, Devin Prouty12, Kristina A. Uban1, Susan Y. Bookheimer1, Mirella Dapretto1, Adriana Galván1, Kara Bagot1, Jay N. Giedd1, M. Alejandra Infante1, Joanna Jacobus1, Kevin Patrick1, Paul D. Shilling1, Rahul S. Desikan1, Yi Li1, Leo P. Sugrue1, Marie T. Banich18, Naomi P. Friedman18, John K. Hewitt18, Christian J. Hopfer18, Joseph T. Sakai18, Jody Tanabe18, Linda B. Cottler19, Sara Jo Nixon19, Linda Chang20, Christine C. Cloak20, Thomas Ernst20, Gloria Reeves20, David N. Kennedy21, Steve Heeringa9, Scott Peltier9, John E. Schulenberg9, Chandra Sripada9, Robert A. Zucker9, William G. Iacono22, Monica Luciana22, Finnegan J. Calabro23, Duncan B. Clark23, David A. Lewis23, Beatriz Luna23, Claudiu Schirda23, Tufikameni Brima24, John J. Foxe24, Edward G. Freedman24, Daniel W. Mruzek24, Michael J. Mason25, Rebekah S. Huber26, Erin McGlade26, Andrew P. Prescot26, Perry F. Renshaw26, Deborah A. Yurgelun-Todd26, Nicholas Allgaier8, Julie A. Dumas8, Masha Y. Ivanova8, Alexandra Potter8, Paul Florsheim27, Christine L. Larson27, Krista M. Lisdahl27, Michael E. Charness28, Bernard F. Fuemmeler7, John M. Hettema7, Joel L. Steinberg7, Andrey P. Anokhin6, Paul E.A. Glaser6, Andrew C. Heath6, Pamela A. F. Madden6, Arielle R. Baskin-Sommers5, R. Todd Constable5, Steven Grant11, Gayathri J. Dowling11, Sandra A. Brown1, Terry L. Jernigan1, Anders M. Dale1 
04 Nov 2018-bioRxiv
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes are described.
Abstract: The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The ABCD Study is a collaborative effort, including a Coordinating Center, 21 data acquisition sites across the United States, and a Data Analysis and Informatics Center (DAIC). The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data will provide a resource of unprecedented scale and depth for studying typical and atypical development. Here, we describe the baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes. Neuroimaging processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI.

276 citations

Journal ArticleDOI
Bader Chaarani1, Sage Hahn1, Nicholas Allgaier1, Shana Adise1  +189 moreInstitutions (38)
TL;DR: In the Adolescent Brain Cognitive Development (ABCD) study as discussed by the authors, the authors report activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657), and working memory and emotion reactivity with an emotional N-back (EN-back) task.
Abstract: The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development. This paper reports activation patterns for fMRI tasks assessing response inhibition, working memory and reward processing obtained at baseline in the longitudinal ABCD Study, providing a reference for research into adolescent brain development.

41 citations

Journal ArticleDOI
TL;DR: The state of the science on cannabis and cannabinoid health effects, both adverse and therapeutic, is reviewed, focusing on the prevalence of use in different populations, the mechanisms by which cannabis exerts its effects, and the double-edged potential of this system to inspire new medications, on one hand, and to cause short and long term harmful effects on the other.

31 citations


Cited by
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TL;DR: In this article , the authors used three of the largest neuroimaging datasets currently available, with a total sample size of around 50,000 individuals, to quantify brain-wide association studies effect sizes and reproducibility as a function of sample size.
Abstract: Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.

611 citations

Journal ArticleDOI
TL;DR: In this paper , the authors used three of the largest neuroimaging datasets currently available, with a total sample size of around 50,000 individuals, to quantify brain-wide association studies effect sizes and reproducibility as a function of sample size.
Abstract: Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.

520 citations

Journal ArticleDOI
Donald J. Hagler1, Sean N. Hatton1, M. Daniela Cornejo1, Carolina Makowski2, Damien A. Fair3, Anthony Steven Dick4, Matthew T. Sutherland4, B. J. Casey5, M Deanna6, Michael P. Harms6, Richard Watts5, James M. Bjork7, Hugh Garavan8, Laura Hilmer1, Christopher J. Pung1, Chelsea S. Sicat1, Joshua M. Kuperman1, Hauke Bartsch1, Feng Xue1, Mary M. Heitzeg9, Angela R. Laird4, Thanh T. Trinh1, Raul Gonzalez4, Susan F. Tapert1, Michael C. Riedel4, Lindsay M. Squeglia10, Luke W. Hyde9, Monica D. Rosenberg5, Eric Earl3, Katia D. Howlett11, Fiona C. Baker12, Mary E. Soules9, Jazmin Diaz1, Octavio Ruiz de Leon1, Wesley K. Thompson1, Michael C. Neale7, Megan M. Herting13, Elizabeth R. Sowell13, Ruben P. Alvarez11, Samuel W. Hawes4, Mariana Sanchez4, Jerzy Bodurka14, Florence J. Breslin14, Amanda Sheffield Morris14, Martin P. Paulus14, W. Kyle Simmons14, Jonathan R. Polimeni15, Andre van der Kouwe15, Andrew S. Nencka16, Kevin M. Gray10, Carlo Pierpaoli11, John A. Matochik11, Antonio Noronha11, Will M. Aklin11, Kevin P. Conway11, Meyer D. Glantz11, Elizabeth Hoffman11, Roger Little11, Marsha F. Lopez11, Vani Pariyadath11, Susan R.B. Weiss11, Dana L. Wolff-Hughes, Rebecca DelCarmen-Wiggins, Sarah W. Feldstein Ewing3, Oscar Miranda-Dominguez3, Bonnie J. Nagel3, Anders Perrone3, Darrick Sturgeon3, Aimee Goldstone12, Adolf Pfefferbaum12, Kilian M. Pohl12, Devin Prouty12, Kristina A. Uban17, Susan Y. Bookheimer18, Mirella Dapretto18, Adriana Galván18, Kara Bagot1, Jay N. Giedd1, M. Alejandra Infante1, Joanna Jacobus1, Kevin Patrick1, Paul D. Shilling1, Rahul S. Desikan19, Yi Li19, Leo P. Sugrue19, Marie T. Banich20, Naomi P. Friedman20, John K. Hewitt20, Christian J. Hopfer20, Joseph T. Sakai20, Jody Tanabe20, Linda B. Cottler21, Sara Jo Nixon21, Linda Chang22, Christine C. Cloak22, Thomas Ernst22, Gloria Reeves22, David N. Kennedy23, Steve Heeringa9, Scott Peltier9, John E. Schulenberg9, Chandra Sripada9, Robert A. Zucker9, William G. Iacono24, Monica Luciana24, Finnegan J. Calabro25, Duncan B. Clark25, David A. Lewis25, Beatriz Luna25, Claudiu Schirda25, Tufikameni Brima26, John J. Foxe26, Edward G. Freedman26, Daniel W. Mruzek26, Michael J. Mason27, Rebekah S. Huber28, Erin McGlade28, Andrew P. Prescot28, Perry F. Renshaw28, Deborah A. Yurgelun-Todd28, Nicholas Allgaier8, Julie A. Dumas8, Masha Y. Ivanova8, Alexandra Potter8, Paul Florsheim29, Christine L. Larson29, Krista M. Lisdahl29, Michael E. Charness30, Michael E. Charness31, Michael E. Charness15, Bernard F. Fuemmeler7, John M. Hettema7, Hermine H. Maes7, Joel L. Steinberg7, Andrey P. Anokhin6, Paul E.A. Glaser6, Andrew C. Heath6, Pamela A. F. Madden6, Arielle R. Baskin-Sommers5, R. Todd Constable5, Steven Grant11, Gayathri J. Dowling11, Sandra A. Brown1, Terry L. Jernigan1, Anders M. Dale1 
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the Adolescent Brain Cognitive Development Study are described to be a resource of unprecedented scale and depth for studying typical and atypical development.

431 citations

Posted ContentDOI
Donald J. Hagler1, Sean N. Hatton1, Carolina Makowski2, M. Daniela Cornejo3, Damien A. Fair3, Anthony Steven Dick4, Matthew T. Sutherland4, B. J. Casey5, M Deanna6, Michael P. Harms6, Richard Watts5, James M. Bjork7, Hugh Garavan8, Laura Hilmer1, Christopher J. Pung1, Chelsea S. Sicat1, Joshua M. Kuperman1, Hauke Bartsch1, Feng Xue1, Mary M. Heitzeg9, Angela R. Laird4, Thanh T. Trinh1, Raul Gonzalez4, Susan F. Tapert1, Michael C. Riedel4, Lindsay M. Squeglia10, Luke W. Hyde9, Monica D. Rosenberg5, Eric Earl3, Katia D. Howlett11, Fiona C. Baker12, Mary E. Soules9, Jazmin Diaz1, Octavio Ruiz de Leon1, Wesley K. Thompson1, Michael C. Neale7, Megan M. Herting13, Elizabeth R. Sowell13, Ruben P. Alvarez14, Samuel W. Hawes4, Mariana Sanchez4, Jerzy Bodurka15, Florence J. Breslin15, Amanda Sheffield Morris15, Martin P. Paulus15, W. Kyle Simmons15, Jonathan R. Polimeni16, Andre van der Kouwe16, Andrew S. Nencka17, Kevin M. Gray10, Carlo Pierpaoli14, John A. Matochik14, Antonio Noronha14, Will M. Aklin11, Kevin P. Conway11, Meyer D. Glantz11, Elizabeth Hoffman11, Roger Little11, Marsha F. Lopez11, Vani Pariyadath11, Susan R.B. Weiss11, Dana L. Wolff-Hughes, Rebecca DelCarmen-Wiggins, Sarah W. Feldstein Ewing3, Oscar Miranda-Dominguez3, Bonnie J. Nagel3, Anders Perrone3, Darrick Sturgeon3, Aimee Goldstone12, Adolf Pfefferbaum12, Kilian M. Pohl12, Devin Prouty12, Kristina A. Uban1, Susan Y. Bookheimer1, Mirella Dapretto1, Adriana Galván1, Kara Bagot1, Jay N. Giedd1, M. Alejandra Infante1, Joanna Jacobus1, Kevin Patrick1, Paul D. Shilling1, Rahul S. Desikan1, Yi Li1, Leo P. Sugrue1, Marie T. Banich18, Naomi P. Friedman18, John K. Hewitt18, Christian J. Hopfer18, Joseph T. Sakai18, Jody Tanabe18, Linda B. Cottler19, Sara Jo Nixon19, Linda Chang20, Christine C. Cloak20, Thomas Ernst20, Gloria Reeves20, David N. Kennedy21, Steve Heeringa9, Scott Peltier9, John E. Schulenberg9, Chandra Sripada9, Robert A. Zucker9, William G. Iacono22, Monica Luciana22, Finnegan J. Calabro23, Duncan B. Clark23, David A. Lewis23, Beatriz Luna23, Claudiu Schirda23, Tufikameni Brima24, John J. Foxe24, Edward G. Freedman24, Daniel W. Mruzek24, Michael J. Mason25, Rebekah S. Huber26, Erin McGlade26, Andrew P. Prescot26, Perry F. Renshaw26, Deborah A. Yurgelun-Todd26, Nicholas Allgaier8, Julie A. Dumas8, Masha Y. Ivanova8, Alexandra Potter8, Paul Florsheim27, Christine L. Larson27, Krista M. Lisdahl27, Michael E. Charness28, Bernard F. Fuemmeler7, John M. Hettema7, Joel L. Steinberg7, Andrey P. Anokhin6, Paul E.A. Glaser6, Andrew C. Heath6, Pamela A. F. Madden6, Arielle R. Baskin-Sommers5, R. Todd Constable5, Steven Grant11, Gayathri J. Dowling11, Sandra A. Brown1, Terry L. Jernigan1, Anders M. Dale1 
04 Nov 2018-bioRxiv
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes are described.
Abstract: The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The ABCD Study is a collaborative effort, including a Coordinating Center, 21 data acquisition sites across the United States, and a Data Analysis and Informatics Center (DAIC). The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data will provide a resource of unprecedented scale and depth for studying typical and atypical development. Here, we describe the baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes. Neuroimaging processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI.

276 citations

Journal ArticleDOI
TL;DR: This Perspective considers three sources of variation that contribute to neurocognitive processing: socioeconomic status, culture and peer environment, and proposes that the field should now move toward studying individual differences.
Abstract: Adolescence is a period of social, psychological and biological development. During adolescence, relationships with others become more complex, peer relationships are paramount and social cognition develops substantially. These psychosocial changes are paralleled by structural and functional changes in the brain. Existing research in adolescent neurocognitive development has focused largely on averages, but this obscures meaningful individual variation in development. In this Perspective, we propose that the field should now move toward studying individual differences. We start by discussing individual variation in structural and functional brain development. To illustrate the importance of considering individual differences in development, we consider three sources of variation that contribute to neurocognitive processing: socioeconomic status, culture and peer environment. To assess individual differences in neurodevelopmental trajectories, large-scale longitudinal datasets are required. Future developmental neuroimaging studies should attempt to characterize individual differences to move toward a more nuanced understanding of neurocognitive changes during adolescence.

274 citations