Abstract
Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization approach for exploratory analysis of task-based fMRI data. Combining the tools of instantaneous phase synchronization and independent component analysis, we characterize whole-brain task-driven responses in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this framework to fMRI data collected during performance of a simple motor task and a social cognitive task. Analyses using an inter-subject phase synchronization approach revealed a large number of brain networks that dynamically synchronized to various features of the task, often not predicted by the hypothesized temporal structure of the task. We suggest that this methodological framework, along with readily available tools in the fMRI community, provides a powerful exploratory, data-driven approach for analysis of task-driven BOLD activity.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 477-488 |
| Number of pages | 12 |
| Journal | NeuroImage |
| Volume | 176 |
| DOIs | |
| State | Published - Aug 1 2018 |
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Keywords
- Brain synchronization
- Exploratory fMRI
- General linear model
- Instantaneous phase analysis
- Inter-subject correlation
- Task fMRI
ASJC Scopus subject areas
- Neurology
- Cognitive Neuroscience
Cite this
Inter-subject phase synchronization for exploratory analysis of task-fMRI. / Bolt, Taylor; Nomi, Jason; Vij, Shruti G.; Chang, Catie; Uddin, Lucina Q.
In: NeuroImage, Vol. 176, 01.08.2018, p. 477-488.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Inter-subject phase synchronization for exploratory analysis of task-fMRI
AU - Bolt, Taylor
AU - Nomi, Jason
AU - Vij, Shruti G.
AU - Chang, Catie
AU - Uddin, Lucina Q
PY - 2018/8/1
Y1 - 2018/8/1
N2 - Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization approach for exploratory analysis of task-based fMRI data. Combining the tools of instantaneous phase synchronization and independent component analysis, we characterize whole-brain task-driven responses in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this framework to fMRI data collected during performance of a simple motor task and a social cognitive task. Analyses using an inter-subject phase synchronization approach revealed a large number of brain networks that dynamically synchronized to various features of the task, often not predicted by the hypothesized temporal structure of the task. We suggest that this methodological framework, along with readily available tools in the fMRI community, provides a powerful exploratory, data-driven approach for analysis of task-driven BOLD activity.
AB - Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization approach for exploratory analysis of task-based fMRI data. Combining the tools of instantaneous phase synchronization and independent component analysis, we characterize whole-brain task-driven responses in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this framework to fMRI data collected during performance of a simple motor task and a social cognitive task. Analyses using an inter-subject phase synchronization approach revealed a large number of brain networks that dynamically synchronized to various features of the task, often not predicted by the hypothesized temporal structure of the task. We suggest that this methodological framework, along with readily available tools in the fMRI community, provides a powerful exploratory, data-driven approach for analysis of task-driven BOLD activity.
KW - Brain synchronization
KW - Exploratory fMRI
KW - General linear model
KW - Instantaneous phase analysis
KW - Inter-subject correlation
KW - Task fMRI
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UR - http://www.scopus.com/inward/citedby.url?scp=85047189620&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2018.04.015
DO - 10.1016/j.neuroimage.2018.04.015
M3 - Article
C2 - 29654878
AN - SCOPUS:85047189620
VL - 176
SP - 477
EP - 488
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
ER -