How delays matter in an oscillatory whole-brain spiking-neuron network model for MEG alpha-rhythms at rest
In recent years the study of the intrinsic brain dynamics in a relaxed awake state in the absence of any specific/ntask has gained increasing attention, as spontaneous neural activity has been found to be highly structured at a/nlarge scale. This so called resting-state activity has been found to be...
| Autores: | , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universitat Pompeu Fabra |
| Repositorio: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/23098 |
| Acceso en línea: | http://hdl.handle.net/10230/23098 http://dx.doi.org/10.1016/j.neuroimage.2013.11.009 |
| Access Level: | acceso abierto |
| Palabra clave: | Resting-state model MEG Delays Spontaneous alpha Alpha-oscillations SFA Spike-frequency adaptation |
| Sumario: | In recent years the study of the intrinsic brain dynamics in a relaxed awake state in the absence of any specific/ntask has gained increasing attention, as spontaneous neural activity has been found to be highly structured at a/nlarge scale. This so called resting-state activity has been found to be comprised by nonrandom spatiotemporal/npatterns and fluctuations, and several Resting-State Networks (RSN) have been found in BOLD-fMRI as well as/nin MEG signal power envelope correlations. The underlying anatomical connectivity structure between areas of/nthe brain has been identified as being a key to the observed functional network connectivity, but the mechanisms/nbehind this are still underdetermined. Theoretical large-scale brain models for fMRI data have corroborated the/nimportance of the connectome in shaping network dynamics,while the importance of delays and noise differ between/nstudies and depend on the models' specific dynamics. In the current study, we present a spiking neuron/nnetworkmodel that is able to produce noisy, distributed alpha-oscillations, matching the power peak in the spectrumof/ngroup resting-stateMEG recordings.We studied howwell the model captured the inter-node correlation/nstructure of the alpha-band power envelopes for different delays between brain areas, and found that the model/nperforms best for propagation delays inside the physiological range (5–10 m/s). Delays also shift the transition/nfrom noisy to bursting oscillations to higher global coupling values in the model. Thus, in contrast to the/nasynchronous fMRI state, delays are important to consider in the presence of oscillation. |
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