Abstract
Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 570-581 |
| Number of pages | 12 |
| Journal | NeuroImage |
| Volume | 179 |
| DOIs | |
| State | Published - Oct 1 2018 |
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Keywords
- Connectivity dynamics
- Functional connectivity
- Steady-state networks
- Working memory
Cite this
Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation. / Tommasin, Silvia; Mascali, Daniele; Moraschi, Marta; Gili, Tommaso; Hassan, Ibrahim Eid; Fratini, Michela; DiNuzzo, Mauro; Wise, Richard G.; Mangia, Silvia; Macaluso, Emiliano; Giove, Federico.
In: NeuroImage, Vol. 179, 01.10.2018, p. 570-581.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation
AU - Tommasin, Silvia
AU - Mascali, Daniele
AU - Moraschi, Marta
AU - Gili, Tommaso
AU - Hassan, Ibrahim Eid
AU - Fratini, Michela
AU - DiNuzzo, Mauro
AU - Wise, Richard G.
AU - Mangia, Silvia
AU - Macaluso, Emiliano
AU - Giove, Federico
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.
AB - Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.
KW - Connectivity dynamics
KW - Functional connectivity
KW - Steady-state networks
KW - Working memory
UR - http://www.scopus.com/inward/record.url?scp=85049478751&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049478751&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2018.06.006
DO - 10.1016/j.neuroimage.2018.06.006
M3 - Article
C2 - 29908935
AN - SCOPUS:85049478751
VL - 179
SP - 570
EP - 581
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
ER -