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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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SSVEP strength versus network properties at group level under 0.28 threshold.(a) The 8 Hz SSVEP strength versus network properties of the stimulus state. (b) The 8 Hz SSVEP strength versus the network properties of the control state. (c) The control network topologies of rat 5 with smallest SSVEP strength and rat 10 with largest SSVEP strength. In (a) ~ (b), the number close to the square dots indicates the rat index, and the SSVEP strength normalization is based on the maximal SSVEP response of the 10 rats, R indicates the correlation coefficients, and p represents the statistical values for the relationship.
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f6: SSVEP strength versus network properties at group level under 0.28 threshold.(a) The 8 Hz SSVEP strength versus network properties of the stimulus state. (b) The 8 Hz SSVEP strength versus the network properties of the control state. (c) The control network topologies of rat 5 with smallest SSVEP strength and rat 10 with largest SSVEP strength. In (a) ~ (b), the number close to the square dots indicates the rat index, and the SSVEP strength normalization is based on the maximal SSVEP response of the 10 rats, R indicates the correlation coefficients, and p represents the statistical values for the relationship.

Mentions: Figure 6(a) visually shows the corresponding relationship between 8 Hz network properties and 8 Hz SSVEP strengths for the group rats under 0.28 threshold. Those relationships revealed in Figure 5(a) and Figure 6(a) are contrary to those obtained from the individual rat as shown in Figure 4(a).


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)

SSVEP strength versus network properties at group level under 0.28 threshold.(a) The 8 Hz SSVEP strength versus network properties of the stimulus state. (b) The 8 Hz SSVEP strength versus the network properties of the control state. (c) The control network topologies of rat 5 with smallest SSVEP strength and rat 10 with largest SSVEP strength. In (a) ~ (b), the number close to the square dots indicates the rat index, and the SSVEP strength normalization is based on the maximal SSVEP response of the 10 rats, R indicates the correlation coefficients, and p represents the statistical values for the relationship.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f6: SSVEP strength versus network properties at group level under 0.28 threshold.(a) The 8 Hz SSVEP strength versus network properties of the stimulus state. (b) The 8 Hz SSVEP strength versus the network properties of the control state. (c) The control network topologies of rat 5 with smallest SSVEP strength and rat 10 with largest SSVEP strength. In (a) ~ (b), the number close to the square dots indicates the rat index, and the SSVEP strength normalization is based on the maximal SSVEP response of the 10 rats, R indicates the correlation coefficients, and p represents the statistical values for the relationship.
Mentions: Figure 6(a) visually shows the corresponding relationship between 8 Hz network properties and 8 Hz SSVEP strengths for the group rats under 0.28 threshold. Those relationships revealed in Figure 5(a) and Figure 6(a) are contrary to those obtained from the individual rat as shown in Figure 4(a).

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