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Plasticity of brain wave network interactions and evolution across physiologic states.

Liu KK, Bartsch RP, Lin A, Mantegna RN, Ivanov PCh - Front Neural Circuits (2015)

Bottom Line: At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions.Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state.These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Network Physiology, Department of Physics, Boston University Boston, MA, USA ; Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School Boston, MA, USA.

ABSTRACT
Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.

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Neural plasticity in the frequency domain represented by reorganization of network interactions across brain areas mediated through a specific frequency band across physiologic states. Network nodes represent six different brain areas: Frontal Fp1 and Fp2 (top vertices of the hexagon), Central C3 and C4 (middle vertices), and Occipital O1 and O2 (bottom vertices). Node colors indicate different frequency bands through which the inter-channel brain interactions are mediated. Group-averaged TDS links strength is represented by line thickness and by different color on gray scale. Only links with % TDS ≥ 45% are shown. Brain interactions mediated through specific frequency bands are associated with very different network structure within a given physiologic state, and exhibit distinct patterns of hierarchical reorganization with transition across physiologic states. Specifically, networks representing brain interactions in the δ and σ band are highly connected and with stronger links in Light Sleep, whereas networks representing brain interactions in the α, γ1, and γ2 band are highly connected and with stronger links during Wake. Notably, network characteristics during Deep Sleep and REM are similar for almost all frequency bands.
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Figure 7: Neural plasticity in the frequency domain represented by reorganization of network interactions across brain areas mediated through a specific frequency band across physiologic states. Network nodes represent six different brain areas: Frontal Fp1 and Fp2 (top vertices of the hexagon), Central C3 and C4 (middle vertices), and Occipital O1 and O2 (bottom vertices). Node colors indicate different frequency bands through which the inter-channel brain interactions are mediated. Group-averaged TDS links strength is represented by line thickness and by different color on gray scale. Only links with % TDS ≥ 45% are shown. Brain interactions mediated through specific frequency bands are associated with very different network structure within a given physiologic state, and exhibit distinct patterns of hierarchical reorganization with transition across physiologic states. Specifically, networks representing brain interactions in the δ and σ band are highly connected and with stronger links in Light Sleep, whereas networks representing brain interactions in the α, γ1, and γ2 band are highly connected and with stronger links during Wake. Notably, network characteristics during Deep Sleep and REM are similar for almost all frequency bands.

Mentions: To better understand the role of same-frequency interactions across brain areas and how these interactions respond to change in physiologic states, we obtain frequency-specific networks (Figure 7) as the ensemble of inter-channel links connecting a specific frequency band at different brain locations (network nodes). We find that brain interactions mediated through specific frequency bands are (i) associated with very different network structure within a given physiologic state, and (ii) exhibit distinct patterns of hierarchical reorganization with transition across physiologic states (Figure 7).


Plasticity of brain wave network interactions and evolution across physiologic states.

Liu KK, Bartsch RP, Lin A, Mantegna RN, Ivanov PCh - Front Neural Circuits (2015)

Neural plasticity in the frequency domain represented by reorganization of network interactions across brain areas mediated through a specific frequency band across physiologic states. Network nodes represent six different brain areas: Frontal Fp1 and Fp2 (top vertices of the hexagon), Central C3 and C4 (middle vertices), and Occipital O1 and O2 (bottom vertices). Node colors indicate different frequency bands through which the inter-channel brain interactions are mediated. Group-averaged TDS links strength is represented by line thickness and by different color on gray scale. Only links with % TDS ≥ 45% are shown. Brain interactions mediated through specific frequency bands are associated with very different network structure within a given physiologic state, and exhibit distinct patterns of hierarchical reorganization with transition across physiologic states. Specifically, networks representing brain interactions in the δ and σ band are highly connected and with stronger links in Light Sleep, whereas networks representing brain interactions in the α, γ1, and γ2 band are highly connected and with stronger links during Wake. Notably, network characteristics during Deep Sleep and REM are similar for almost all frequency bands.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4620446&req=5

Figure 7: Neural plasticity in the frequency domain represented by reorganization of network interactions across brain areas mediated through a specific frequency band across physiologic states. Network nodes represent six different brain areas: Frontal Fp1 and Fp2 (top vertices of the hexagon), Central C3 and C4 (middle vertices), and Occipital O1 and O2 (bottom vertices). Node colors indicate different frequency bands through which the inter-channel brain interactions are mediated. Group-averaged TDS links strength is represented by line thickness and by different color on gray scale. Only links with % TDS ≥ 45% are shown. Brain interactions mediated through specific frequency bands are associated with very different network structure within a given physiologic state, and exhibit distinct patterns of hierarchical reorganization with transition across physiologic states. Specifically, networks representing brain interactions in the δ and σ band are highly connected and with stronger links in Light Sleep, whereas networks representing brain interactions in the α, γ1, and γ2 band are highly connected and with stronger links during Wake. Notably, network characteristics during Deep Sleep and REM are similar for almost all frequency bands.
Mentions: To better understand the role of same-frequency interactions across brain areas and how these interactions respond to change in physiologic states, we obtain frequency-specific networks (Figure 7) as the ensemble of inter-channel links connecting a specific frequency band at different brain locations (network nodes). We find that brain interactions mediated through specific frequency bands are (i) associated with very different network structure within a given physiologic state, and (ii) exhibit distinct patterns of hierarchical reorganization with transition across physiologic states (Figure 7).

Bottom Line: At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions.Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state.These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Network Physiology, Department of Physics, Boston University Boston, MA, USA ; Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School Boston, MA, USA.

ABSTRACT
Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.

Show MeSH