Exploring the network dynamics underlying brain activity during rest
Open accessAbstract
Since the mid 1990s, the intriguing dynamics of the brain at rest has been attracting a growing body of research in neuroscience. Neuroimaging studies have revealed distinct functional networks that slowly activate and deactivate, pointing to the existence of an underlying network dynamics emerging spontaneously during rest, with specific spatial, temporal and spectral characteristics. Several theoretical scenarios have been proposed and tested with the use of large-scale computational models of coupled brain areas. However, a mechanistic explanation that encompasses all the phenomena observed in the brain during rest is still to come. In this review, we provide an overview of the key findings of resting-state activity covering a range of neuroimaging modalities including fMRI, EEG and MEG. We describe how to best define and analyze anatomical and functional brain networks and how unbalancing these networks may lead to problems with mental health. Finally, we review existing large-scale models of resting-state dynamics in health and disease. An important common feature of resting-state models is that the emergence of resting-state functional networks is obtained when the model parameters are such that the system operates at the edge of a bifurcation. At this critical working point, the global network dynamics reveals correlation patterns that are spatially shaped by the underlying anatomical structure, leading to an optimal fit with the empirical BOLD functional connectivity. However, new insights coming from recent studies, including faster oscillatory dynamics and non-stationary functional connectivity, must be taken into account in future models to fully understand the network mechanisms leading to the resting-state activity.
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This conceptualization incorporates the understanding of whole brain networks as dynamic entities whose activity and connectivity shift with situational demands.
“this conceptualization takes into account our increasing understanding of these whole brain networks as dynamic entities, with patterns of activity and connectivity (both within-network and with other networks) shifting as required by ever-changing situational demands (Cabral, Kringelbach, & Deco, 2014;Shine et al., 2016).”
From Mental Time Travel? A Neurocognitive Model of Event Simulation. (2020) · cites this paper as Cabral, Kringelbach, & Deco, 2014
Our conclusions are tempered by questions about the origins and significance of correlated fluctuations in the BOLD fMRI signal.
“Like other studies focused on measures of functional connectivity, our conclusions are tempered by questions about the origins and significance of correlated fluctuations in the blood-oxygen-level dependent (BOLD) fMRI signal61-63.”
From Evolutionarily conserved prefrontal-amygdalar dysfunction in early-life anxiety (2014) · cites this paper as [62]
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de Miras, J. R., Toscano, F. S., Iglesias‐Parro, S., Ibáñez-Molina, A. J., Casali, A. G., Laureys, S., Massimini, M., Esteban, F. J., Navas, J., & Langa, J. A. (2019) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2019.04.017 · Cited by 42 · see citing works
Neuroscience of Reward, Motivation, and Drive
Kringelbach, M. L., & Berridge, K. C. (2016) · Advances in motivation and achievement · doi:10.1108/s0749-742320160000019020 · Cited by 42 · see citing works
Self-citationKlingner, C., Volk, G., Brodoehl, S., Witte, O., & Guntinas-Lichius, O. (2014) · NeuroImage: Clinical · doi:10.1016/j.nicl.2014.08.011 · Cited by 40 · see citing works
- Authors
- Cabral, J., Kringelbach, M. L., & Deco, G.
- Affiliations
- Universitat Pompeu Fabra (ES)
- Aarhus University (DK)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Corresponding author
- Cabral, Joana
- Venue
- Progress in Neurobiology
- Publisher
- Elsevier BV
- Published
- 2014-03
- Volume
- 114
- Pages
- 102-131
- ISSN
- 0301-0082 (ISSN-L)
- OpenAlex
- W1973272857
- Cited by
- 351
- References
- 254
- Citations by year
- 2026: 14 · 2025: 24 · 2024: 35 · 2023: 25 · 2022: 29 · 2021: 28 · 2020: 28 · 2019: 25 · 2018: 33 · 2017: 34 · 2016: 27 · 2015: 35 · 2014: 14
- FWCI
- 3.54
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Progress in Neurobiology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by-nc-nd)
- Funders
- ERC Advanced Grant DYSTRUCTURE (295129)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- resting-state brain activity, network dynamics, functional brain networks, bifurcation, criticality, EEG, MEG, functional MRI, oscillatory dynamics, mental health
- MeSH terms
- Animals, Brain, Humans, Neural Pathways, Rest, Nonlinear Dynamics, Neuroimaging
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