Spatiotemporal dynamics of maximal and minimal EEG spectral power

Abstract

Oscillatory neural activities are prevalent in the brain with their phase realignment contributing to the coordination of neural communication. Phase realignments may have especially strong (or weak) impact when neural activities are strongly synchronized (or desynchronized) within the interacting populations. We report that the spatiotemporal dynamics of strong regional synchronization measured as maximal EEG spectral power—referred to as activation—and strong regional desynchronization measured as minimal EEG spectral power—referred to as suppression—are characterized by the spatial segregation of small-scale and large-scale networks. Specifically, small-scale spectral-power activations and suppressions involving only 2–7% (1–4 of 60) of EEG scalp sites were prolonged (relative to stochastic dynamics) and consistently co-localized in a frequency specific manner. For example, the small-scale networks for θ, α, β1, and β2 bands (4–30 Hz) consistently included frontal sites when the eyes were closed, whereas the small-scale network for γ band (31–55 Hz) consistently clustered in medial-central-posterior sites whether the eyes were open or closed. Large-scale activations and suppressions involving over 17–30% (10–18 of 60) of EEG sites were also prolonged and generally clustered in regions complementary to where small-scale activations and suppressions clustered. In contrast, intermediate-scale activations and suppressions (involving 7–17% of EEG sites) tended to follow stochastic dynamics and were less consistently localized. These results suggest that strong synchronizations and desynchronizations tend to occur in small-scale and large-scale networks that are spatially segregated and frequency specific. These synchronization networks may broadly segregate the relatively independent and highly cooperative oscillatory processes while phase realignments fine-tune the network configurations based on behavioral demands.

Characteristics of spontaneous anterior-posterior oscillation-frequency convergences in the alpha band

“…Although taking the temporal derivative of EEG ( ∆,,-∆) , where ∆𝑡 is the temporal resolution, i.e., 1/512 sec here) would completely neutralize the 1/𝑓 * component only when 𝛽 = 1, the method worked well for our data (Menceloglu et al, 2020a(Menceloglu et al, , 2021a(Menceloglu et al, , 2021b(Menceloglu et al, , 2021c, suggesting that 𝛽~1 generally held for our data. As we discussed in our prior reports (Menceloglu et al, 2021a(Menceloglu et al, , 2021b(Menceloglu et al, , 2021c, taking EEG temporal derivative offers additional advantages. For example, EEG temporal derivatives are drift free.…”

“…Note that β in the 1/ f β spectral background varies around 1 (see [53] for a review of the various factors that influence β , and [54] for contributions of the excitatory and inhibitory neural dynamics to β ). Although taking the temporal derivative of EEG , where Δt is the temporal resolution, i.e., 1/512 sec here) would completely neutralize the 1/ f β component only when β = 1, the method worked well for our data [32,34-36], suggesting that β ∼1 generally held for our data. As we discussed in our prior reports [34-36], taking EEG temporal derivative offers additional advantages.…”

“…Although taking the temporal derivative of EEG , where Δt is the temporal resolution, i.e., 1/512 sec here) would completely neutralize the 1/ f β component only when β = 1, the method worked well for our data [32,34-36], suggesting that β ∼1 generally held for our data. As we discussed in our prior reports [34-36], taking EEG temporal derivative offers additional advantages. For example, EEG temporal derivatives are drift free.…”

“…A generic nature video was presented on a 13-inch, 2017 MacBook Pro 2880(H)-by-1800(V)-pixelresolution LCD monitor with normal brightness and contrast settings, placed 100 cm in front of participants, subtending approximately 16° (H)-by-10° (V) of visual angle. Subsets of these data were previously analyzed for different purposes [32][33][34][35][36].…”

A phase-shifting anterior-posterior network organizes global phase relations

“…Participants p29-p52 (N = 24) participated in the replication of the rest-with-eyes-closed condition and subsequently participated in a rest-witheyes-open-in-the-dark condition which was the same as the former except that the room was darkened and participants kept their eyes open while blinking naturally. Subsets or the whole of these data were previously analyzed for different purposes [22][23][24][25].…”