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Plasticity of brain wave network interactions and evolution across physiologic states - PubMed

  • ️Thu Jan 01 2015

Plasticity of brain wave network interactions and evolution across physiologic states

Kang K L Liu et al. Front Neural Circuits. 2015.

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.

Keywords: brain wave interactions; network physiology; neural plasticity; sleep; time delay stability.

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Figures

Figure 1
Figure 1

Schematic presentation of the Time Delay Stability (TDS) method and TDS matrix representing the degree of coupling between different frequency bands across brain locations. (A) Segments of brain EEG power spectra Sδ and Sσ for the δ- and σ-band shown for four consecutive 60 s time windows. (B) Coordinated bursts in Sδ and Sσ lead to pronounced cross-correlation Cδσ within each time window. The time lag τ0 that corresponds to the peak in the cross-correlation function Cδσ(τ) represents the time delay between the two signals. (C) Time delay τ0 between Sδ and Sσ plotted as a function of time for consecutive 60 s windows moving with a step of 30 s. Four red dots represent τ0 for the four windows shown in the above panels. Note the transition at ~1200 s from a segment with strongly fluctuating τ0 to a stable time delay regime with τ0 ≈ constant. Such regime of time delay stability (TDS) indicates the onset of physiological coupling. The fraction of time when TDS is observed in the EEG recording, i.e., % TDS, quantifies the degree of coupling strength. Longer periods of TDS between Sδ and Sσ reflect stronger coupling. (D) TDS matrix representing the degree of coupling between different physiologically relevant EEG frequency bands (δ, θ, α, σ, β, γ1, γ2) derived from the C3 channel. Matrix elements represent % TDS, where the color code is shown in the vertical bar. (E) Block-matrix representing the degree of TDS coupling between EEG channels (Fp1, Fp2, C3, C4, O1, O2) and between EEG frequency bands. Each off-diagonal block element corresponds to a specific pair of EEG channels and each diagonal block element represents the coupling between different frequency bands within the same EEG channel, as shown in (D).

Figure 2
Figure 2

Transitions in the Time Delay Stability (TDS) matrix across physiologic states indicate neural response and plasticity in brain wave interactions at the integrated level. Group-averaged Time Delay Stability (TDS) block-matrices during distinct physiologic states (sleep stages) obtained from continuous 8-h EEG recordings during sleep from 36 healthy subjects. Color code represents the average strength of TDS coupling between brain waves (distinct EEG frequency bands) across different brain locations as quantified by % TDS—i.e., the fraction of time out of the total duration of a given sleep stage throughout the night when TDS is observed. Parallel diagonal lines across each off-diagonal matrix block indicate strong coupling between the same EEG frequency band derived from different EEG-channel locations (e.g., coupling of δC3–δC4, αO1–αO2 etc.). This behavior is consistently observed for all sleep stages indicating that a significant part of the brain-brain interactions across different brain areas are mediated through coupling between the same frequency bands. Transitions in the TDS matrix across different sleep stages are associated with reorganization in brain-network connectivity as reflected by (i) different configurations in the strength of the off-diagonal matrix elements that represent coupling between different EEG frequency bands in both the diagonal and off-diagonal matrix blocks, and (ii) the overall strength of coupling (% TDS, shown by color code)—lower connectivity during Deep Sleep and REM, higher during Light Sleep and highest brain-network connectivity in Wake. Such complex reorganization in the strength of brain interactions (represented by network links in the following figures) across different frequency bands and brain locations demonstrates remarkable plasticity of the brain-network in response to change of physiologic state and function.

Figure 3
Figure 3

Rank distribution of the strength of network links connecting different brain waves across brain areas. Group averaged coupling strength of inter-channel network links between different brain areas represented by the matrix elements in the off-diagonal matrix blocks of the TDS matrix shown in Figure 2 is ranked separately for different sleep stages. Rank 1 corresponds to the strongest link in the network with highest degree of Time Delay Stability (TDS) between a pair of brain waves. The rank distributions for different sleep stages are characterized by different strength of the network links measured in % TDS—consistently lower values for most links during Deep Sleep, higher values during REM and highest during Light Sleep and Wake. Magenta dashed line represents a threshold of 45% TDS. Notably, links above the 45% TDS threshold exhibit two distinct forms of rank distributions—fast decay for Deep Sleep and REM vs. much slower decay for Light Sleep and Wake.

Figure 4
Figure 4

Neural plasticity represented by transitions in the sub-networks of brain wave interactions centered at the Central C3 channel. Network nodes with different colors represent seven different frequency bands (δ, θ, α, σ, β, γ1, γ2) derived from EEG signals. Each set of seven nodes ordered as a heptagon forms a vertex on the hexagon representing six EEG channels from particular brain locations: Two Frontal areas (Fp1 and Fp2), two Central areas (C3 and C4), and two Occipital areas (O1 and O2). Interactions between frequency bands derived from the C3 channel (intra-channel links) are color-coded in gray scale. Interactions between frequency bands derived from the C3 channel and network nodes in all other EEG channels are represented by inter-channel links shown with the same color as the corresponding frequency band (network node) at C3. Line thickness represents the group-averaged link strength as measured by % TDS, and only links with % TDS ≥ 45% are shown (threshold in Figure 3). Both the intra-channel networks (involving links between the frequency nodes at C3) and inter-channel networks (colored links between nodes at C3 and nodes at all other channels) undergo complex hierarchical reorganization across sleep stages, indicating pronounced plasticity in the way frequency bands communicate locally within the C3 Central area and with frequency bands at other brain areas. The intra-channel subnetwork at C3 exhibits low connectivity during REM, medium connectivity during Wake and Light Sleep, and becomes highly connected during Deep Sleep. A similar sleep-stage pattern is also observed for the intra-channel links strength. In contrast, the inter-channel subnetwork between C3 and other brain areas undergoes a very different transition in network connectivity and link strength—from low connectivity in REM and Deep Sleep to high connectivity in Light Sleep and Wake. Note that an identical network structure and reorganization across sleep stages is observed for the Central C4 channel (not shown), indicating a robust symmetry between the left and right hemisphere.

Figure 5
Figure 5

Neural plasticity represented by transitions in the sub-networks of brain interactions centered at the Frontal Fp1 channel. Network nodes and network links are illustrated in the same way as described in Figure 4. Line thickness represents the group-averaged link strength as measured by % TDS, and only links with % TDS ≥ 45% are shown. Intra-channel sub-networks (links in gray scale) between different frequency nodes at the Fp1 channel exhibit high connectivity and link strength in all sleep stages. This is in contrast to the pronounced stratification in connectivity and average link strength observed for the C3 intra-channel sub-networks shown in Figure 4, and indicates a reduced plasticity in the intra-channel communications within the Frontal Fp1 area. A very different behavior is exhibited by the inter-channel sub-network representing interactions between frequency nodes at the Fp1 location and frequency nodes at other brain areas, which is characterized by a pronounced reorganization in both global connectivity and link strength configurations: Deep Sleep and REM are characterized by low global connectivity of the inter-channel sub-network and dominant links between Fp1 and the neighboring Frontal and Central areas; in contrast, global connectivity is high during Wake and Light Sleep with emerging Frontal-Occipital links that are predominantly mediated through the high frequency bands during Wake (red color links) and mainly through the low frequency bands during Light Sleep (blue color links). Note that an identical network structure and reorganization across sleep stages is observed for the Frontal Fp2 channel (not shown), indicating a robust symmetry between the left and right hemisphere.

Figure 6
Figure 6

Neural plasticity represented by transitions in the sub-networks of brain interactions centered at the Occipital O1 channel. Network nodes and network links are illustrated in the same way as described in Figures 4, 5. Line thickness represents the group-averaged link strength as measured by % TDS, and only links with % TDS ≥ 45% are shown. In contrast to the intra-channel sub-networks of brain interactions across frequency bands within the Central C3 area (Figure 4) and within the Frontal Fp1 area (Figure 5), the intra-channel sub-networks at the Occipital O1 channel have weak links and are generally less connected for all sleep stages—very low connectivity during REM and Light Sleep, slightly higher during Deep Sleep and highest during Wake. In contrast to the intra-channel sub-networks at the Occipital O1 location, the inter-channel sub-networks associated with the O1 channel exhibit pronounced sleep-stage stratification in global connectivity and average link strength—low connectivity during Deep Sleep and REM, and higher connectivity during Light Sleep and Wake, where brain interactions are predominantly mediated through low frequency bands during Light Sleep (blue color links) and through the high frequency bands during Wake (red color links). A similar sleep-stage stratification pattern in the overall connectivity and average link strength of the inter-channel sub-network is consistently observed for the Central C3 and Frontal Fp1 channels (Figures 4, 5) indicating a general rule of network reorganization underlying neural plasticity in brain interactions between frequency bands across brain areas. Note that an identical network structure and reorganization across sleep stages is observed for both O1 and O2 channels, indicating a robust symmetry between the left and right hemisphere that is also observed for the frontal and central channels (Figures 4, 5).

Figure 7
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.

Figure 8
Figure 8

Sleep-stage stratification patterns in the average strength of inter-channel brain interactions mediated through specific frequency bands. Average link strength in the frequency-specific networks of inter-channel interactions shown in Figure 7 are grouped by sleep stages (A) and by frequency bands (B), respectively. (A) demonstrates the degree of involvement of different frequency bands in inter-channel brain communications in each physiologic state (sleep stage). In Deep Sleep inter-channel interactions are mainly mediated through the lowest frequency δ band, while in Light Sleep both the δ band and the mid-frequency σ band associated with sleep spindle activity dominate the interactions between different brain areas. For REM sleep, the average link strength of inter-channel brain networks is similar for all frequency bands. In contrast, during Wake the α band and the high-frequency γ1 and γ2 bands dominate the inter-channel brain interactions. (B) Average link strength of brain network interactions mediated through different frequency bands exhibit distinct sleep-stage stratification patterns. For brain network interactions in the high-frequency β, γ1, γ2 bands, the average link strength is high during Wake, lower during REM and Light Sleep, and lowest during Deep Sleep. In contrast, the interactions in the mid- and low-frequency bands are characterized by different sleep-stage stratification in the average link strength—indicating pronounced plasticity of brain network interactions in the frequency domain.

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