The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Optimal Information Transfer in the Cortex through Synchronization
Open accessAbstract
In recent experimental work it has been shown that neuronal interactions are modulated by neuronal synchronization and that this modulation depends on phase shifts in neuronal oscillations. This result suggests that connections in a network can be shaped through synchronization. Here, we test and expand this hypothesis using a model network. We use transfer entropy, an information theoretical measure, to quantify the exchanged information. We show that transferred information depends on the phase relation of the signal, that the amount of exchanged information increases as a function of oscillations in the signal and that the speed of the information transfer increases as a function of synchronization. This implies that synchronization makes information transport more efficient. In summary, our results reinforce the hypothesis that synchronization modulates neuronal interactions and provide further evidence that gamma band synchronization has behavioral relevance.
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Cites
A mechanism for cognitive dynamics: neuronal communication through neuronal coherence.
Fries, P. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.08.011 · Cited by 4,284
Gray, C. M., König, P., Engel, A. K., & Singer, W. (1989) · Nature · doi:10.1038/338334a0 · Cited by 4,183
Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices
Buschman, T. J., & Miller, E. K. (2007) · Science · doi:10.1126/science.1138071 · Cited by 2,380
Gamma rhythms and beta rhythms have different synchronization properties
Kopell, N., Ermentrout, G. B., Whittington, M. A., & Traub, R. D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.4.1867 · Cited by 1,072 · cited 1×
“Several methods have been proposed to generate beta oscillations [24,25].”
MethodBrunel, N., & Wang, X.-J. (2001) · Journal of Computational Neuroscience · doi:10.1023/a:1011204814320 · Cited by 620
Cited by
Attentional stimulus selection through selective synchronization between monkey visual areas
Bosman, C. A., Schoffelen, J.-M., Brunet, N., Oostenveld, R., Bastos, A. M., Womelsdorf, T., Rubehn, B., Stieglitz, T., De Weerd, P., & Fries, P. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.037 · Cited by 720
Mechanisms of deep brain stimulation
Herrington, T. M., Cheng, J. J., & Eskandar, E. N. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00281.2015 · Cited by 551
Intrinsic Coupling Modes: Multiscale Interactions in Ongoing Brain Activity
Engel, A. K., Gerloff, C., Hilgetag, C. C., & Nolte, G. (2013) · Neuron · doi:10.1016/j.neuron.2013.09.038 · Cited by 471
Oscillations in the prefrontal cortex: a gateway to memory and attention
Benchenane, K., Tiesinga, P. H., & Battaglia, F. P. (2011) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2011.01.004 · Cited by 366
Data based identification and prediction of nonlinear and complex dynamical systems
Wang, W.-X., Lai, Y.-C., & Grebogi, C. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.06.004 · Cited by 299
Metadata
- Authors
- Buehlmann, A., & Deco, G.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-09-16
- Volume
- 6
- Issue
- 9
- Pages
- e1000934
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W2024487789
- Cited by
- 167
- References
- 5
- FWCI
- 8.15
- Type
- journal article
- Language
- en
- Open access
- gold
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