Association Between Fractional Amplitude of Low-Frequency Spontaneous Fluctuation and Degree Centrality in Children and Adolescents

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Arquivos
art_SATO_Association_Between_Fractional_Amplitude_of_LowFrequency_Spontaneous_Fluctuation_2019.PDF (17.61 MB)
Citações na Scopus
7
Tipo de produção
article
Data de publicação
2019
Editora
MARY ANN LIEBERT, INC
DOI
Indexadores
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Autores
JR, Claudinei Eduardo Biazoli
MOURA, Luciana Monteiro
CROSSLEY, Nicolas
ZUGMAN, Andre
PICON, Felipe Almeida
ROHDE, Luis Augusto
Autor de Grupo de pesquisa
Editores
Coordenadores
Organizadores
Citação
BRAIN CONNECTIVITY, v.9, n.5, p.379-387, 2019
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
The fractional amplitude of low-frequency fluctuations (fALFFs) of the BOLD signal have been successfully applied as exploratory tools in neuroimaging. This metric has been useful in mapping brain functional changes in many clinical populations. However, little is known about the neurophysiological correlates of fALFF. This study aimed at demonstrating that fALFF is related to local network centrality during childhood and adolescence. The establishment of this relationship is fundamental to provide a more meaningful explanation to previous clinical and neurodevelopmental studies based on fALFF. Our findings show a correlation of similar to 0.5 between these two metrics at a group level, which is a finding replicated in four large independent samples. However, when considering the across-subject and intra-subject correlations between the two metrics, the correlation is much lower, probably due to the low signal-to-noise ratio. Moreover, we found that regions with high fALFF and degree centrality overlapped modestly, particularly the posterior cingulate/precuneus and lateral parietal cortices.
Palavras-chave
children, connectivity, fMRI, network, neurodevelopment, resting-state
URI
https://observatorio.fm.usp.br/handle/OPI/33061
Referências
  1. Aiello M, 2015, NEUROIMAGE, V113, P111, DOI 10.1016/j.neuroimage.2015.03.017
  2. Bernier M, 2017, NEUROIMAGE, V150, P14, DOI 10.1016/j.neuroimage.2017.01.055
  3. Birn RM, 2008, HUM BRAIN MAPP, V29, P740, DOI 10.1002/hbm.20577
  4. Birn RM, 2014, BRAIN CONNECT, V4, P511, DOI 10.1089/brain.2014.0284
  5. Birn RM, 2009, NEUROIMAGE, V47, P1092, DOI 10.1016/j.neuroimage.2009.05.030
  6. BISWAL B, 1995, MAGNET RESON MED, V34, P537, DOI 10.1002/mrm.1910340409
  7. Biswal BB, 2010, P NATL ACAD SCI USA, V107, P4734, DOI 10.1073/pnas.0911855107
  8. Buckner RL, 2007, NEUROIMAGE, V37, P1091, DOI 10.1016/j.neuroimage.2007.01.010
  9. Buckner RL, 2009, J NEUROSCI, V29, P1860, DOI 10.1523/JNEUROSCI.5062-08.2009
  10. Bullmore ET, 2009, NAT REV NEUROSCI, V10, P186, DOI 10.1038/nrn2575
  11. Buzsaki G, 2004, SCIENCE, V304, P1926, DOI 10.1126/science.1099745
  12. Cordes D, 2001, AM J NEURORADIOL, V22, P1326
  13. Cox RW, 2012, NEUROIMAGE, V62, P743, DOI 10.1016/j.neuroimage.2011.08.056
  14. Di Martino A, 2014, NEURON, V83, P1335, DOI 10.1016/j.neuron.2014.08.050
  15. Di X, 2013, FRONT HUM NEUROSCI, V7, DOI 10.3389/fnhum.2013.00118
  16. Fox MD, 2007, NAT REV NEUROSCI, V8, P700, DOI 10.1038/nrn2201
  17. Fransson P, 2005, HUM BRAIN MAPP, V26, P15, DOI 10.1002/hbm.20113
  18. Goodman R, 2000, J CHILD PSYCHOL PSYC, V41, P645, DOI 10.1111/j.1469-7610.2000.tb02345.x
  19. Gordon EM, 2016, CEREB CORTEX, V26, P288, DOI 10.1093/cercor/bhu239
  20. Han Y, 2011, NEUROIMAGE, V55, P287, DOI 10.1016/j.neuroimage.2010.11.059
  21. He BYJ, 2008, P NATL ACAD SCI USA, V105, P16039, DOI 10.1073/pnas.0807010105
  22. He Y, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0005226
  23. Jenkinson M, 2012, NEUROIMAGE, V62, P782, DOI 10.1016/j.neuroimage.2011.09.015
  24. Meda SA, 2015, SCHIZOPHRENIA BULL, V41, P1336, DOI 10.1093/schbul/sbv064
  25. Murphy K, 2009, NEUROIMAGE, V44, P893, DOI 10.1016/j.neuroimage.2008.09.036
  26. Nugent AC, 2015, J CEREBR BLOOD F MET, V35, P583, DOI 10.1038/jcbfm.2014.228
  27. Power JD, 2012, NEUROIMAGE, V59, P2142, DOI 10.1016/j.neuroimage.2011.10.018
  28. Salum GA, 2015, INT J METH PSYCH RES, V24, P58, DOI 10.1002/mpr.1459
  29. Sato JR, 2016, DEV COGN NEUROS-NETH, V20, P2, DOI 10.1016/j.dcn.2016.05.002
  30. Satterthwaite TD, 2015, CURR OPIN NEUROBIOL, V30, P85, DOI 10.1016/j.conb.2014.10.005
  31. Shehzad Z, 2009, CEREB CORTEX, V19, P2209, DOI 10.1093/cercor/bhn256
  32. Shmueli K, 2007, NEUROIMAGE, V38, P306, DOI 10.1016/j.neuroimage.2007.07.037
  33. Smith SM, 2009, P NATL ACAD SCI USA, V106, P13040, DOI 10.1073/pnas.0905267106
  34. TELLEGEN A, 1967, J CONSULT PSYCHOL, V31, P499, DOI 10.1037/h0024963
  35. van den Heuvel MP, 2010, EUR NEUROPSYCHOPHARM, V20, P519, DOI 10.1016/j.euroneuro.2010.03.008
  36. Van Dijk KRA, 2010, J NEUROPHYSIOL, V103, P297, DOI 10.1152/jn.00783.2009
  37. Wang GZ, 2015, NEURON, V88, P659, DOI 10.1016/j.neuron.2015.10.022
  38. Wang L, 2016, NEUROSCI LETT, V614, P105, DOI 10.1016/j.neulet.2016.01.012
  39. Xu K, 2014, J AFFECT DISORDERS, V152, P237, DOI 10.1016/j.jad.2013.09.017
  40. Xu YJ, 2015, BIOMED RES INT, DOI 10.1155/2015/204628
  41. Yan CG, 2013, NEUROIMAGE, V76, P183, DOI 10.1016/j.neuroimage.2013.03.004
  42. Yu RJ, 2014, HUM BRAIN MAPP, V35, P627, DOI 10.1002/hbm.22203
  43. Zhong WJ, 2016, DIAGN INTERV RADIOL, V22, P196, DOI 10.5152/dir.2015.15208
  44. Zou QH, 2008, J NEUROSCI METH, V172, P137, DOI 10.1016/j.jneumeth.2008.04.012
  45. Zuo XN, 2010, NEUROIMAGE, V49, P1432, DOI 10.1016/j.neuroimage.2009.09.037

Coleções
Artigos e Materiais de Revistas Científicas - FM/MDR
Artigos e Materiais de Revistas Científicas - FM/MPS
Artigos e Materiais de Revistas Científicas - LIM/23
Artigos e Materiais de Revistas Científicas - LIM/44