Abstract
Functional neuroimaging data was collected while postpartum women and age-matched control women performed the Remember/Know judgment task in the functional magnetic resonance imaging scanner. This data provides information about functional connectivity patterns across the subjective recollection networks that were informative in differentiating the postpartum women from control women. Classification performances based on machine learning algorithms and descriptions of functional connectivity patterns that derived the peak classification accuracy are reported in this article. All other results from our study have been reported in Nah et al. (2018) [1].
Original language | English |
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Pages (from-to) | 1142-1147 |
Number of pages | 6 |
Journal | Data in Brief |
Volume | 19 |
DOIs | |
Publication status | Published - 2018 Aug |
Bibliographical note
Funding Information:This study was supported by the National Research Foundation of Korea Grant funded by the Korean Government ( NRF-2014R1A1A2055116 ) and faculty research grants from Yonsei University College of Medicine ( 4-2013-0111 ). The authors declare no competing financial interests.
Funding Information:
This study was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014R1A1A2055116) and faculty research grants from Yonsei University College of Medicine (4-2013-0111). The authors declare no competing financial interests.
Publisher Copyright:
© 2018 The Authors
All Science Journal Classification (ASJC) codes
- General