Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

John R. Pruett; Sridhar Kandala; Sarah Hoertel; Abraham Z. Snyder; Jed T. Elison; Tomoyuki Nishino; Eric Feczko; Nico U.F. Dosenbach; Binyam Nardos; Jonathan D. Power; Babatunde Adeyemo; Kelly N. Botteron; Robert C. McKinstry; Alan C. Evans; Heather C. Hazlett; Stephen R. Dager; Sarah Paterson; Robert T. Schultz; D. Louis Collins; Vladimir S. Fonov; Martin Styner; Guido Gerig; Samir Das; Penelope Kostopoulos; John N. Constantino; Annette M. Estes; Steven E. Petersen; Bradley L. Schlaggar; Joseph Piven

doi:10.1016/j.dcn.2015.01.003

Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

John R. Pruett, Sridhar Kandala, Sarah Hoertel, Abraham Z. Snyder, Jed T. Elison, Tomoyuki Nishino, Eric Feczko, Nico U.F. Dosenbach, Binyam Nardos, Jonathan D. Power, Babatunde Adeyemo, Kelly N. Botteron, Robert C. McKinstry, Alan C. Evans, Heather C. Hazlett, Stephen R. Dager, Sarah Paterson, Robert T. Schultz, D. Louis Collins, Vladimir S. FonovMartin Styner, Guido Gerig, Samir Das, Penelope Kostopoulos, John N. Constantino, Annette M. Estes, Steven E. Petersen, Bradley L. Schlaggar, Joseph Piven

Biomedical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

Original language	English (US)
Pages (from-to)	123-133
Number of pages	11
Journal	Developmental Cognitive Neuroscience
Volume	12
DOIs	https://doi.org/10.1016/j.dcn.2015.01.003
State	Published - Apr 2015

Keywords

Development
Functional brain networks
Functional connectivity magnetic resonance imaging (fcMRI)
Infant
Multivariate pattern analysis (MVPA)
Support vector machine (SVM)

ASJC Scopus subject areas

Cognitive Neuroscience

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Pruett, J. R., Kandala, S., Hoertel, S., Snyder, A. Z., Elison, J. T., Nishino, T., Feczko, E., Dosenbach, N. U. F., Nardos, B., Power, J. D., Adeyemo, B., Botteron, K. N., McKinstry, R. C., Evans, A. C., Hazlett, H. C., Dager, S. R., Paterson, S., Schultz, R. T., Collins, D. L., ... Piven, J. (2015). Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data. Developmental Cognitive Neuroscience, 12, 123-133. https://doi.org/10.1016/j.dcn.2015.01.003

Pruett, JR, Kandala, S, Hoertel, S, Snyder, AZ, Elison, JT, Nishino, T, Feczko, E, Dosenbach, NUF, Nardos, B, Power, JD, Adeyemo, B, Botteron, KN, McKinstry, RC, Evans, AC, Hazlett, HC, Dager, SR, Paterson, S, Schultz, RT, Collins, DL, Fonov, VS, Styner, M, Gerig, G, Das, S, Kostopoulos, P, Constantino, JN, Estes, AM, Petersen, SE, Schlaggar, BL & Piven, J 2015, 'Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data', Developmental Cognitive Neuroscience, vol. 12, pp. 123-133. https://doi.org/10.1016/j.dcn.2015.01.003

@article{cb792f1cf44d441194bd394f41b6df92,

title = "Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data",

abstract = "Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.",

keywords = "Development, Functional brain networks, Functional connectivity magnetic resonance imaging (fcMRI), Infant, Multivariate pattern analysis (MVPA), Support vector machine (SVM)",

author = "Pruett, {John R.} and Sridhar Kandala and Sarah Hoertel and Snyder, {Abraham Z.} and Elison, {Jed T.} and Tomoyuki Nishino and Eric Feczko and Dosenbach, {Nico U.F.} and Binyam Nardos and Power, {Jonathan D.} and Babatunde Adeyemo and Botteron, {Kelly N.} and McKinstry, {Robert C.} and Evans, {Alan C.} and Hazlett, {Heather C.} and Dager, {Stephen R.} and Sarah Paterson and Schultz, {Robert T.} and Collins, {D. Louis} and Fonov, {Vladimir S.} and Martin Styner and Guido Gerig and Samir Das and Penelope Kostopoulos and Constantino, {John N.} and Estes, {Annette M.} and Petersen, {Steven E.} and Schlaggar, {Bradley L.} and Joseph Piven",

note = "Publisher Copyright: {\textcopyright} 2015 The Authors. Published by Elsevier Ltd.",

year = "2015",

month = apr,

doi = "10.1016/j.dcn.2015.01.003",

language = "English (US)",

volume = "12",

pages = "123--133",

journal = "Developmental Cognitive Neuroscience",

issn = "1878-9293",

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AU - Pruett, John R.

AU - Kandala, Sridhar

AU - Hoertel, Sarah

AU - Snyder, Abraham Z.

AU - Elison, Jed T.

AU - Nishino, Tomoyuki

AU - Feczko, Eric

AU - Dosenbach, Nico U.F.

AU - Nardos, Binyam

AU - Power, Jonathan D.

AU - Adeyemo, Babatunde

AU - Botteron, Kelly N.

AU - McKinstry, Robert C.

AU - Evans, Alan C.

AU - Hazlett, Heather C.

AU - Dager, Stephen R.

AU - Paterson, Sarah

AU - Schultz, Robert T.

AU - Collins, D. Louis

AU - Fonov, Vladimir S.

AU - Styner, Martin

AU - Gerig, Guido

AU - Das, Samir

AU - Kostopoulos, Penelope

AU - Constantino, John N.

AU - Estes, Annette M.

AU - Petersen, Steven E.

AU - Schlaggar, Bradley L.

AU - Piven, Joseph

PY - 2015/4

Y1 - 2015/4

N2 - Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

AB - Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

KW - Development

KW - Functional brain networks

KW - Functional connectivity magnetic resonance imaging (fcMRI)

KW - Infant

KW - Multivariate pattern analysis (MVPA)

KW - Support vector machine (SVM)

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JO - Developmental Cognitive Neuroscience

JF - Developmental Cognitive Neuroscience

ER -

Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

Abstract

Keywords

ASJC Scopus subject areas

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