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Cortical network properties revealed by SSVEP in anesthetized rats.

Xu P, Tian C, Zhang Y, Jing W, Wang Z, Liu T, Hu J, Tian Y, Xia Y, Yao D - Sci Rep (2013)

Bottom Line: Steady state visual evoked potentials (SSVEP) are assumed to be regulated by multiple brain areas, yet the underlying mechanisms are not well understood.In this study, we utilized multi-channel intracranial recordings together with network analysis to investigate the underlying relationships between SSVEP and brain networks in anesthetized rat.All these aspects consistently indicate that SSVEP response is closely correlated with network properties, the reorganization of the background network plays a crucial role in SSVEP production, and the background network may provide a physiological marker for evaluating the potential of SSVEP generation.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.

ABSTRACT
Steady state visual evoked potentials (SSVEP) are assumed to be regulated by multiple brain areas, yet the underlying mechanisms are not well understood. In this study, we utilized multi-channel intracranial recordings together with network analysis to investigate the underlying relationships between SSVEP and brain networks in anesthetized rat. We examined the relationship between SSVEP amplitude and the network topological properties for different stimulation frequencies, the synergetic dynamic changes of the amplitude and topological properties in each rat, the network properties of the control state, and the individual difference of SSVEP network attributes existing among rats. All these aspects consistently indicate that SSVEP response is closely correlated with network properties, the reorganization of the background network plays a crucial role in SSVEP production, and the background network may provide a physiological marker for evaluating the potential of SSVEP generation.

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The relationships of SSVEP strength and network properties at group level for various thresholds (0.10 ~ 0.28).(a) SSVEP strength versus 8 Hz stimulus network properties; (b) SSVEP strength versus control network properties. In (a) ~ (b), the x-axis is the threshold, and y-axis is the corresponding correlation coefficients for the four network properties.
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f5: The relationships of SSVEP strength and network properties at group level for various thresholds (0.10 ~ 0.28).(a) SSVEP strength versus 8 Hz stimulus network properties; (b) SSVEP strength versus control network properties. In (a) ~ (b), the x-axis is the threshold, and y-axis is the corresponding correlation coefficients for the four network properties.

Mentions: In the experiment, though all the rats are fostered at the same time, they still have a quite different SSVEP strength. For each threshold, the topological properties and SSVEP strengths under the 8 Hz stimulus state are averaged over all segments selected for each rat. The detailed relationships between 8 Hz network properties and 8 Hz SSVEP strengths among group rats for the various thresholds (0.10 ~ 0.28) are given in below Figure 5(a), where the strong correlations between the 8 Hz-SSVEP strength and the four network properties are observed, with negative correlations for C, Ge and Le, and a positive correlation for L.


Cortical network properties revealed by SSVEP in anesthetized rats.

Xu P, Tian C, Zhang Y, Jing W, Wang Z, Liu T, Hu J, Tian Y, Xia Y, Yao D - Sci Rep (2013)

The relationships of SSVEP strength and network properties at group level for various thresholds (0.10 ~ 0.28).(a) SSVEP strength versus 8 Hz stimulus network properties; (b) SSVEP strength versus control network properties. In (a) ~ (b), the x-axis is the threshold, and y-axis is the corresponding correlation coefficients for the four network properties.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750539&req=5

f5: The relationships of SSVEP strength and network properties at group level for various thresholds (0.10 ~ 0.28).(a) SSVEP strength versus 8 Hz stimulus network properties; (b) SSVEP strength versus control network properties. In (a) ~ (b), the x-axis is the threshold, and y-axis is the corresponding correlation coefficients for the four network properties.
Mentions: In the experiment, though all the rats are fostered at the same time, they still have a quite different SSVEP strength. For each threshold, the topological properties and SSVEP strengths under the 8 Hz stimulus state are averaged over all segments selected for each rat. The detailed relationships between 8 Hz network properties and 8 Hz SSVEP strengths among group rats for the various thresholds (0.10 ~ 0.28) are given in below Figure 5(a), where the strong correlations between the 8 Hz-SSVEP strength and the four network properties are observed, with negative correlations for C, Ge and Le, and a positive correlation for L.

Bottom Line: Steady state visual evoked potentials (SSVEP) are assumed to be regulated by multiple brain areas, yet the underlying mechanisms are not well understood.In this study, we utilized multi-channel intracranial recordings together with network analysis to investigate the underlying relationships between SSVEP and brain networks in anesthetized rat.All these aspects consistently indicate that SSVEP response is closely correlated with network properties, the reorganization of the background network plays a crucial role in SSVEP production, and the background network may provide a physiological marker for evaluating the potential of SSVEP generation.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.

ABSTRACT
Steady state visual evoked potentials (SSVEP) are assumed to be regulated by multiple brain areas, yet the underlying mechanisms are not well understood. In this study, we utilized multi-channel intracranial recordings together with network analysis to investigate the underlying relationships between SSVEP and brain networks in anesthetized rat. We examined the relationship between SSVEP amplitude and the network topological properties for different stimulation frequencies, the synergetic dynamic changes of the amplitude and topological properties in each rat, the network properties of the control state, and the individual difference of SSVEP network attributes existing among rats. All these aspects consistently indicate that SSVEP response is closely correlated with network properties, the reorganization of the background network plays a crucial role in SSVEP production, and the background network may provide a physiological marker for evaluating the potential of SSVEP generation.

Show MeSH